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add results folder

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Ricardo Montañana Gómez
2021-04-11 02:24:03 +02:00
parent dd83175508
commit 603c73a476
23 changed files with 1202 additions and 1 deletions
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results/normalizados/base_raf.sql Normal file
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replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:20:51', 'crossval', 0.706738, 'balance-scale', 'BaseRaF', 1, 0, '{}', 0.230848, 0.0318996, 0.0178062, 28.81);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:20:52', 'crossval', 0.605, 'balloons', 'BaseRaF', 1, 0, '{}', 0.230195, 0.0011394, 0.000448618, 4.65);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:21:06', 'crossval', 0.965694, 'breast-cancer-wisc-diag', 'BaseRaF', 1, 0, '{}', 0.0143465, 0.0149353, 0.00289327, 10.81);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:21:12', 'crossval', 0.74485, 'breast-cancer-wisc-prog', 'BaseRaF', 1, 0, '{}', 0.0541356, 0.00703754, 0.000955761, 16.44);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:21:27', 'crossval', 0.942857, 'breast-cancer-wisc', 'BaseRaF', 1, 0, '{}', 0.0166086, 0.0151967, 0.0017186, 28.89);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:21:40', 'crossval', 0.656438, 'breast-cancer', 'BaseRaF', 1, 0, '{}', 0.0500531, 0.0192996, 0.00201731, 64.88);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:25:14', 'crossval', 0.774788, 'cardiotocography-10clases', 'BaseRaF', 1, 0, '{}', 0.0179435, 0.42372, 0.111354, 255.01);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:27:36', 'crossval', 0.896715, 'cardiotocography-3clases', 'BaseRaF', 1, 0, '{}', 0.0129992, 0.381444, 0.0666812, 106.66);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:27:41', 'crossval', 0.772981, 'conn-bench-sonar-mines-rocks', 'BaseRaF', 1, 0, '{}', 0.054519, 0.00598101, 0.000759466, 13.5);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:02', 'crossval', 0.675117, 'cylinder-bands', 'BaseRaF', 1, 0, '{}', 0.0359021, 0.0249964, 0.00202589, 47.54);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:13', 'crossval', 0.970723, 'dermatology', 'BaseRaF', 1, 0, '{}', 0.0175846, 0.0121389, 0.0010901, 13.93);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:18', 'crossval', 0.753522, 'echocardiogram', 'BaseRaF', 1, 0, '{}', 0.0718413, 0.00750033, 0.00161811, 20.14);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:21', 'crossval', 0.798, 'fertility', 'BaseRaF', 1, 0, '{}', 0.0787592, 0.00438735, 0.00082982, 15.92);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:31', 'crossval', 0.720133, 'haberman-survival', 'BaseRaF', 1, 0, '{}', 0.0475346, 0.0131448, 0.00499674, 32.68);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:43', 'crossval', 0.779804, 'heart-hungarian', 'BaseRaF', 1, 0, '{}', 0.0445811, 0.0166187, 0.00157407, 50.97);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:28:47', 'crossval', 0.773671, 'hepatitis', 'BaseRaF', 1, 0, '{}', 0.0639841, 0.00578021, 0.000831726, 16.34);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:29:13', 'crossval', 0.696685, 'ilpd-indian-liver', 'BaseRaF', 1, 0, '{}', 0.0356957, 0.0304009, 0.010731, 78.23);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:29:22', 'crossval', 0.875389, 'ionosphere', 'BaseRaF', 1, 0, '{}', 0.0343367, 0.00810207, 0.00126368, 14.86);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:29:25', 'crossval', 0.953413, 'iris', 'BaseRaF', 1, 0, '{}', 0.0312751, 0.00319496, 0.000564433, 10.65);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:30:28', 'crossval', 0.70178, 'led-display', 'BaseRaF', 1, 0, '{}', 0.0236684, 0.0837334, 0.00515429, 133.27);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:31:24', 'crossval', 0.726722, 'libras', 'BaseRaF', 1, 0, '{}', 0.0462516, 0.194452, 0.0319483, 65);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:31:49', 'crossval', 0.790875, 'low-res-spect', 'BaseRaF', 1, 0, '{}', 0.0338948, 0.0700037, 0.00737621, 22.25);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:31:54', 'crossval', 0.761622, 'lymphography', 'BaseRaF', 1, 0, '{}', 0.072691, 0.00602972, 0.000858306, 17.09);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:32:50', 'crossval', 0.780206, 'mammographic', 'BaseRaF', 1, 0, '{}', 0.0261463, 0.0725665, 0.00665848, 177.33);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:32:52', 'crossval', 0.667239, 'molec-biol-promoter', 'BaseRaF', 1, 0, '{}', 0.0894839, 0.00204324, 0.000882715, 4.23);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:33:10', 'crossval', 0.834034, 'musk-1', 'BaseRaF', 1, 0, '{}', 0.0355503, 0.0294025, 0.00582493, 32.15);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:33:59', 'crossval', 0.792313, 'oocytes_merluccius_nucleus_4d', 'BaseRaF', 1, 0, '{}', 0.0236722, 0.0609631, 0.00810882, 76.76);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:34:47', 'crossval', 0.910551, 'oocytes_merluccius_states_2f', 'BaseRaF', 1, 0, '{}', 0.0178087, 0.0589824, 0.00537782, 46.61);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:35:27', 'crossval', 0.76193, 'oocytes_trisopterus_nucleus_2f', 'BaseRaF', 1, 0, '{}', 0.0290605, 0.0437252, 0.00599953, 84.37);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:36:01', 'crossval', 0.922149, 'oocytes_trisopterus_states_5b', 'BaseRaF', 1, 0, '{}', 0.016058, 0.0338147, 0.0038348, 28.44);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:36:06', 'crossval', 0.87924, 'parkinsons', 'BaseRaF', 1, 0, '{}', 0.0434764, 0.00664538, 0.000956323, 18.21);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:36:50', 'crossval', 0.697005, 'pima', 'BaseRaF', 1, 0, '{}', 0.0329339, 0.0598898, 0.00405292, 179.02);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:36:54', 'crossval', 0.81136, 'pittsburg-bridges-MATERIAL', 'BaseRaF', 1, 0, '{}', 0.0721078, 0.00614998, 0.000956048, 18.21);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:36:59', 'crossval', 0.622107, 'pittsburg-bridges-REL-L', 'BaseRaF', 1, 0, '{}', 0.0836926, 0.0107519, 0.00245178, 33.92);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:04', 'crossval', 0.630217, 'pittsburg-bridges-SPAN', 'BaseRaF', 1, 0, '{}', 0.0855243, 0.0103792, 0.00144035, 32.74);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:07', 'crossval', 0.821007, 'pittsburg-bridges-T-OR-D', 'BaseRaF', 1, 0, '{}', 0.071734, 0.00451751, 0.000865693, 15.6);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:16', 'crossval', 0.590586, 'planning', 'BaseRaF', 1, 0, '{}', 0.0720305, 0.0149104, 0.00202668, 49.52);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:21', 'crossval', 0.539375, 'post-operative', 'BaseRaF', 1, 0, '{}', 0.102817, 0.00860377, 0.00125772, 28.27);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:25', 'crossval', 0.942518, 'seeds', 'BaseRaF', 1, 0, '{}', 0.0293366, 0.00587637, 0.000679482, 14.71);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:37:27', 'crossval', 0.678261, 'statlog-australian-credit', 'BaseRaF', 1, 0, '{}', 0.0319213, 0.00851742, 0.00101665, 1);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:38:23', 'crossval', 0.68762, 'statlog-german-credit', 'BaseRaF', 1, 0, '{}', 0.0285632, 0.0759742, 0.00988248, 118.37);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:38:33', 'crossval', 0.747605, 'statlog-heart', 'BaseRaF', 1, 0, '{}', 0.0505201, 0.01431, 0.00186931, 34.9);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:41:32', 'crossval', 0.953604, 'statlog-image', 'BaseRaF', 1, 0, '{}', 0.0428999, 0.459961, 0.209446, 91.85);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:42:14', 'crossval', 0.789572, 'statlog-vehicle', 'BaseRaF', 1, 0, '{}', 0.0290904, 0.0418569, 0.00252999, 79.05);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:42:32', 'crossval', 0.971567, 'synthetic-control', 'BaseRaF', 1, 0, '{}', 0.0148618, 0.0233277, 0.00241783, 15.44);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:42:58', 'crossval', 0.974906, 'tic-tac-toe', 'BaseRaF', 1, 0, '{}', 0.0119599, 0.0372124, 0.00723869, 21.49);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:43:10', 'crossval', 0.822601, 'vertebral-column-2clases', 'BaseRaF', 1, 0, '{}', 0.0397492, 0.016375, 0.00309965, 45.54);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:43:13', 'crossval', 0.97748, 'wine', 'BaseRaF', 1, 0, '{}', 0.020518, 0.00259591, 0.000401448, 6.86);
replace into results (date, time, type, accuracy, dataset, classifier, norm, stand, parameters, accuracy_std, time_spent, time_spent_std, nodes) values ('2021-04-10', '01:43:15', 'crossval', 0.936262, 'zoo', 'BaseRaF', 1, 0, '{}', 0.0494478, 0.00416789, 0.00034269, 13.2);

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replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:19','crossval','0.7820799999999999','0.03608203985364464','balance-scale','cart','1','0','0.0006873464584350586','6.056292602707366e-05','{}','256.8','128.9','10.72');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:19','crossval','0.6833333333333335','0.26977356760397747','balloons','cart','1','0','0.0004589319229125977','6.682214388089997e-05','{}','11.36','6.18','3.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:20','crossval','0.9239217512808571','0.02323176886368342','breast-cancer-wisc-diag','cart','1','0','0.004066610336303711','0.00037735371598770866','{}','36.16','18.58','7.1');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:20','crossval','0.6919743589743588','0.07238575982092108','breast-cancer-wisc-prog','cart','1','0','0.0016518211364746093','0.00016523387709218434','{}','43.2','22.1','7.84');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:20','crossval','0.9434984583761563','0.02073055093670967','breast-cancer-wisc','cart','1','0','0.000748910903930664','6.367492730058185e-05','{}','57.52','29.26','8.72');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:20','crossval','0.6359225650332728','0.0534792000241946','breast-cancer','cart','1','0','0.0006718873977661133','8.342001699012386e-05','{}','164.72','82.86','15.56');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:20','crossval','0.8105368682684342','0.019247308169627633','cardiotocography-10clases','cart','1','0','0.009399790763854981','0.000310402623122502','{}','480.84','240.92','20.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.9203670809168737','0.01396855482026071','cardiotocography-3clases','cart','1','0','0.00814661979675293','0.0005860086312648286','{}','210.96','105.98','15.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.7258768873403021','0.0682090752129407','conn-bench-sonar-mines-rocks','cart','1','0','0.0025511789321899414','0.0002510580336619537','{}','34.16','17.58','6.44');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.7130211307824103','0.04627911197423834','cylinder-bands','cart','1','0','0.0021189451217651367','0.000164014995951283','{}','131.96','66.48','13.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.9396038504257683','0.02387579095888003','dermatology','cart','1','0','0.0007885885238647461','0.00011540453341909482','{}','34.6','17.8','10.82');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.7458404558404559','0.080776687074494','echocardiogram','cart','1','0','0.0005904006958007813','6.0040661402099946e-05','{}','32.6','16.8','8.82');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.7989999999999999','0.08395832299420945','fertility','cart','1','0','0.0004935407638549805','7.218480550167721e-05','{}','28.84','14.92','7.16');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.6382178741406662','0.05575144578993558','haberman-survival','cart','1','0','0.0006317853927612305','7.359752923339246e-05','{}','160.92','80.96','15.1');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:21','crossval','0.7502746931618937','0.044645868130612026','heart-hungarian','cart','1','0','0.0007543468475341797','8.493027944498374e-05','{}','83.08','42.04','9.6');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.7658064516129032','0.07350593002050229','hepatitis','cart','1','0','0.0006294441223144531','7.136307121991442e-05','{}','37.0','19.0','7.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.6625906277630415','0.03822153903302792','ilpd-indian-liver','cart','1','0','0.0015907526016235352','0.00010613849153297268','{}','186.32','93.66','18.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.8757907444668007','0.03797437861573896','ionosphere','cart','1','0','0.0031133270263671874','0.0004496306989895815','{}','40.32','20.66','9.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.94','0.043716256828679995','iris','cart','1','0','0.0004883623123168946','6.707633932216357e-05','{}','15.08','8.04','5.04');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.7037','0.029644729717101474','led-display','cart','1','0','0.0006838130950927734','7.497018504393881e-05','{}','156.6','78.8','7.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:22','crossval','0.6547222222222221','0.05983580929572253','libras','cart','1','0','0.00954397201538086','0.00041554126865619165','{}','132.32','66.66','11.16');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:23','crossval','0.8352036677834599','0.030503013555880365','low-res-spect','cart','1','0','0.01601393222808838','0.001041629752684619','{}','74.96','37.98','8.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:23','crossval','0.7690114942528736','0.0755835919787076','lymphography','cart','1','0','0.0005543041229248047','7.206299803216294e-05','{}','49.0','25.0','7.86');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:23','crossval','0.7557739637305698','0.02089031159057769','mammographic','cart','1','0','0.0009842538833618165','8.02737307480172e-05','{}','403.12','202.06','20.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:24','crossval','0.7158008658008658','0.08811757165025375','molec-biol-promoter','cart','1','0','0.0007098007202148437','9.733050797678472e-05','{}','22.24','11.62','5.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:25','crossval','0.777530701754386','0.04335321566037286','musk-1','cart','1','0','0.018938016891479493','0.0023793265663644494','{}','75.12','38.06','12.5');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:25','crossval','0.7196642754662842','0.03071950171876295','oocytes_merluccius_nucleus_4d','cart','1','0','0.013992009162902832','0.0011456969136993383','{}','222.24','111.62','15.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:26','crossval','0.8911927307508368','0.02477313298773685','oocytes_merluccius_states_2f','cart','1','0','0.007075467109680176','0.000580046153013565','{}','98.84','49.92','10.78');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:26','crossval','0.7257617246141836','0.029837690053299604','oocytes_trisopterus_nucleus_2f','cart','1','0','0.008345584869384765','0.00042809521443671906','{}','192.76','96.88','15.64');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.8702630156728517','0.025916263242401694','oocytes_trisopterus_states_5b','cart','1','0','0.009247007369995118','0.0004790588538986512','{}','109.12','55.06','12.56');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.8558974358974359','0.05822037527622443','parkinsons','cart','1','0','0.0010352849960327149','9.855723737448487e-05','{}','24.84','12.92','5.54');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.7009116373822256','0.031101392763464096','pima','cart','1','0','0.001743307113647461','0.00010421535409735057','{}','218.52','109.76','14.28');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.8006493506493506','0.07641918889128255','pittsburg-bridges-MATERIAL','cart','1','0','0.0004951238632202148','6.908799856069978e-05','{}','33.24','17.12','7.18');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.6143333333333333','0.09787364013413712','pittsburg-bridges-REL-L','cart','1','0','0.0005135631561279297','6.495038402721139e-05','{}','57.72','29.36','12.18');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.5564912280701755','0.09603550008778475','pittsburg-bridges-SPAN','cart','1','0','0.0005118465423583985','7.031496030423733e-05','{}','55.36','28.18','10.1');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.8234761904761905','0.08723519697826523','pittsburg-bridges-T-OR-D','cart','1','0','0.0004817628860473633','7.016788984381056e-05','{}','26.44','13.72','5.94');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.573963963963964','0.07834935548163284','planning','cart','1','0','0.0010381507873535156','0.00011806603047514821','{}','60.56','30.78','12.18');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.5822222222222222','0.10554970744033704','post-operative','cart','1','0','0.0005062770843505859','7.122806409227687e-05','{}','66.32','33.66','11.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.9157142857142857','0.042380952380952366','seeds','cart','1','0','0.0006688928604125976','6.788828620597182e-05','{}','25.04','13.02','6.14');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:27','crossval','0.572463768115942','0.040476058097881','statlog-australian-credit','cart','1','0','0.0019480609893798829','0.00011803304739191946','{}','269.88','135.44','18.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:28','crossval','0.6899','0.025129464777428084','statlog-german-credit','cart','1','0','0.0021873950958251954','9.371859211329562e-05','{}','331.92','166.46','16.42');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:28','crossval','0.7351851851851852','0.045699861775011355','statlog-heart','cart','1','0','0.0007651948928833008','6.677668508558311e-05','{}','73.68','37.34','8.86');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:28','crossval','0.9616017316017317','0.009472609323341975','statlog-image','cart','1','0','0.008970613479614259','0.0003288094001180248','{}','127.32','64.16','15.94');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:28','crossval','0.7063849634528365','0.030574747774242836','statlog-vehicle','cart','1','0','0.003118605613708496','0.00014468487911691033','{}','233.52','117.26','16.26');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:29','crossval','0.9023333333333332','0.02511307760244982','synthetic-control','cart','1','0','0.00933086395263672','0.00039118840253255936','{}','52.16','26.58','8.58');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:29','crossval','0.9522851221640489','0.018529859619663462','tic-tac-toe','cart','1','0','0.0008065223693847657','9.298620463823368e-05','{}','119.2','60.1','9.28');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:29','crossval','0.7996774193548387','0.04231712199258938','vertebral-column-2clases','cart','1','0','0.0008004426956176758','9.684473759962773e-05','{}','61.16','31.08','9.3');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:29','crossval','0.9015873015873015','0.0526003102936011','wine','cart','1','0','0.0007057809829711915','6.556413493732969e-05','{}','16.24','8.62','4.38');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:41:29','crossval','0.9555714285714286','0.044427856881917915','zoo','cart','1','0','0.0004845094680786133','6.487745318311946e-05','{}','17.96','9.48','6.8');

55
results/normalizados/cart.txt Normal file
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* Process all datasets set with cart: tanveer norm: True std: False store in: cart
5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
Dataset Samp Var Cls Nodes Leaves Depth Accuracy Time Parameters
============================== ===== === === ======= ======= ======= =============== =============== ==========
balance-scale 625 4 3 256.80 128.90 10.72 0.782080±0.0361 0.000687±0.0001 {}
balloons 16 4 2 11.36 6.18 3.46 0.683333±0.2698 0.000459±0.0001 {}
breast-cancer-wisc-diag 569 30 2 36.16 18.58 7.10 0.923922±0.0232 0.004067±0.0004 {}
breast-cancer-wisc-prog 198 33 2 43.20 22.10 7.84 0.691974±0.0724 0.001652±0.0002 {}
breast-cancer-wisc 699 9 2 57.52 29.26 8.72 0.943498±0.0207 0.000749±0.0001 {}
breast-cancer 286 9 2 164.72 82.86 15.56 0.635923±0.0535 0.000672±0.0001 {}
cardiotocography-10clases 2126 21 10 480.84 240.92 20.02 0.810537±0.0192 0.009400±0.0003 {}
cardiotocography-3clases 2126 21 3 210.96 105.98 15.88 0.920367±0.0140 0.008147±0.0006 {}
conn-bench-sonar-mines-rocks 208 60 2 34.16 17.58 6.44 0.725877±0.0682 0.002551±0.0003 {}
cylinder-bands 512 35 2 131.96 66.48 13.46 0.713021±0.0463 0.002119±0.0002 {}
dermatology 366 34 6 34.60 17.80 10.82 0.939604±0.0239 0.000789±0.0001 {}
echocardiogram 131 10 2 32.60 16.80 8.82 0.745840±0.0808 0.000590±0.0001 {}
fertility 100 9 2 28.84 14.92 7.16 0.799000±0.0840 0.000494±0.0001 {}
haberman-survival 306 3 2 160.92 80.96 15.10 0.638218±0.0558 0.000632±0.0001 {}
heart-hungarian 294 12 2 83.08 42.04 9.60 0.750275±0.0446 0.000754±0.0001 {}
hepatitis 155 19 2 37.00 19.00 7.66 0.765806±0.0735 0.000629±0.0001 {}
ilpd-indian-liver 583 9 2 186.32 93.66 18.08 0.662591±0.0382 0.001591±0.0001 {}
ionosphere 351 33 2 40.32 20.66 9.88 0.875791±0.0380 0.003113±0.0004 {}
iris 150 4 3 15.08 8.04 5.04 0.940000±0.0437 0.000488±0.0001 {}
led-display 1000 7 10 156.60 78.80 7.00 0.703700±0.0296 0.000684±0.0001 {}
libras 360 90 15 132.32 66.66 11.16 0.654722±0.0598 0.009544±0.0004 {}
low-res-spect 531 100 9 74.96 37.98 8.74 0.835204±0.0305 0.016014±0.0010 {}
lymphography 148 18 4 49.00 25.00 7.86 0.769011±0.0756 0.000554±0.0001 {}
mammographic 961 5 2 403.12 202.06 20.46 0.755774±0.0209 0.000984±0.0001 {}
molec-biol-promoter 106 57 2 22.24 11.62 5.24 0.715801±0.0881 0.000710±0.0001 {}
musk-1 476 166 2 75.12 38.06 12.50 0.777531±0.0434 0.018938±0.0024 {}
oocytes_merluccius_nucleus_4d 1022 41 2 222.24 111.62 15.08 0.719664±0.0307 0.013992±0.0011 {}
oocytes_merluccius_states_2f 1022 25 3 98.84 49.92 10.78 0.891193±0.0248 0.007075±0.0006 {}
oocytes_trisopterus_nucleus_2f 912 25 2 192.76 96.88 15.64 0.725762±0.0298 0.008346±0.0004 {}
oocytes_trisopterus_states_5b 912 32 3 109.12 55.06 12.56 0.870263±0.0259 0.009247±0.0005 {}
parkinsons 195 22 2 24.84 12.92 5.54 0.855897±0.0582 0.001035±0.0001 {}
pima 768 8 2 218.52 109.76 14.28 0.700912±0.0311 0.001743±0.0001 {}
pittsburg-bridges-MATERIAL 106 7 3 33.24 17.12 7.18 0.800649±0.0764 0.000495±0.0001 {}
pittsburg-bridges-REL-L 103 7 3 57.72 29.36 12.18 0.614333±0.0979 0.000514±0.0001 {}
pittsburg-bridges-SPAN 92 7 3 55.36 28.18 10.10 0.556491±0.0960 0.000512±0.0001 {}
pittsburg-bridges-T-OR-D 102 7 2 26.44 13.72 5.94 0.823476±0.0872 0.000482±0.0001 {}
planning 182 12 2 60.56 30.78 12.18 0.573964±0.0783 0.001038±0.0001 {}
post-operative 90 8 3 66.32 33.66 11.24 0.582222±0.1055 0.000506±0.0001 {}
seeds 210 7 3 25.04 13.02 6.14 0.915714±0.0424 0.000669±0.0001 {}
statlog-australian-credit 690 14 2 269.88 135.44 18.46 0.572464±0.0405 0.001948±0.0001 {}
statlog-german-credit 1000 24 2 331.92 166.46 16.42 0.689900±0.0251 0.002187±0.0001 {}
statlog-heart 270 13 2 73.68 37.34 8.86 0.735185±0.0457 0.000765±0.0001 {}
statlog-image 2310 18 7 127.32 64.16 15.94 0.961602±0.0095 0.008971±0.0003 {}
statlog-vehicle 846 18 4 233.52 117.26 16.26 0.706385±0.0306 0.003119±0.0001 {}
synthetic-control 600 60 6 52.16 26.58 8.58 0.902333±0.0251 0.009331±0.0004 {}
tic-tac-toe 958 9 2 119.20 60.10 9.28 0.952285±0.0185 0.000807±0.0001 {}
vertebral-column-2clases 310 6 2 61.16 31.08 9.30 0.799677±0.0423 0.000800±0.0001 {}
wine 178 13 3 16.24 8.62 4.38 0.901587±0.0526 0.000706±0.0001 {}
zoo 101 16 7 17.96 9.48 6.80 0.955571±0.0444 0.000485±0.0001 {}
Time: 0h 0m 9s

49
results/normalizados/j48svm.sql Normal file
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insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'balance-scale', 0.94, 0.021836, 0.14862, 0.054757, 35.6);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'balloons', 0.595, 0.187831, 0.00504, 0.002683, 4.4);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'breast-cancer-wisc-diag', 0.952878, 0.023749, 0.03688, 0.007506, 13.48);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'breast-cancer-wisc-prog', 0.724038, 0.072215, 0.03234, 0.006895, 21.52);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'breast-cancer-wisc', 0.967674, 0.012478, 0.04816, 0.006961, 8.28);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'breast-cancer', 0.707719, 0.052367, 0.0713, 0.010275, 23.16);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'cardiotocography-10clases', 0.830812, 0.016194, 1.42148, 0.089646, 197.6);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'cardiotocography-3clases', 0.927327, 0.013055, 0.40532, 0.018162, 92.24);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'conn-bench-sonar-mines-rocks', 0.73892, 0.06386, 0.04418, 0.005117, 25.2);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'cylinder-bands', 0.726351, 0.029474, 0.1099, 0.0079, 85.4);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'dermatology', 0.955735, 0.023581, 0.0738, 0.016643, 15.12);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'echocardiogram', 0.805527, 0.084433, 0.02296, 0.005407, 13.4);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'fertility', 0.857, 0.071421, 0.02498, 0.005998, 4.48);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'haberman-survival', 0.714056, 0.04944, 0.02248, 0.010216, 4.44);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'heart-hungarian', 0.785026, 0.048182, 0.06344, 0.006888, 22.12);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'hepatitis', 0.761935, 0.058025, 0.03602, 0.005464, 16.6);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'ilpd-indian-liver', 0.690339, 0.04248, 0.05586, 0.011349, 14.24);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'ionosphere', 0.891984, 0.033857, 0.0462, 0.0036, 23.64);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'iris', 0.947333, 0.035957, 0.0133, 0.002914, 7.04);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'led-display', 0.7204, 0.028193, 1.31958, 0.102793, 13.04);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'libras', 0.66, 0.062869, 1.09746, 0.078557, 88.24);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'low-res-spect', 0.83358, 0.038622, 0.34854, 0.027053, 45.8);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'lymphography', 0.778552, 0.078755, 0.0553, 0.009578, 25.28);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'mammographic', 0.821435, 0.024479, 0.09182, 0.011567, 18.68);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'molec-biol-promoter', 0.744935, 0.092023, 0.02698, 0.004701, 16.0);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'musk-1', 0.82693, 0.046843, 0.32902, 0.029412, 50.72);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'oocytes_merluccius_nucleus_4d', 0.741766, 0.034628, 0.23738, 0.025296, 78.04);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'oocytes_merluccius_states_2f', 0.901374, 0.021463, 0.12582, 0.017535, 38.36);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'oocytes_trisopterus_nucleus_2f', 0.756587, 0.034538, 0.2026, 0.047357, 57.56);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'oocytes_trisopterus_states_5b', 0.887943, 0.02368, 0.1566, 0.015336, 56.12);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'parkinsons', 0.844615, 0.051642, 0.02474, 0.004582, 18.04);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'pima', 0.749876, 0.026553, 0.06754, 0.012694, 22.68);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'pittsburg-bridges-MATERIAL', 0.855844, 0.070512, 0.04744, 0.009731, 7.12);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'pittsburg-bridges-REL-L', 0.645048, 0.103969, 0.0741, 0.013543, 13.52);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'pittsburg-bridges-SPAN', 0.621579, 0.123278, 0.05116, 0.010828, 10.7);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'pittsburg-bridges-T-OR-D', 0.838333, 0.077644, 0.02828, 0.00596, 6.72);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'planning', 0.711381, 0.050453, 0.0074, 0.003504, 1.08);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'post-operative', 0.701111, 0.086702, 0.0495, 0.013578, 1.88);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'seeds', 0.909524, 0.049027, 0.02798, 0.006433, 13.28);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'statlog-australian-credit', 0.66029, 0.03596, 0.17408, 0.022439, 85.16);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'statlog-german-credit', 0.7244, 0.028664, 0.23886, 0.01523, 127.24);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'statlog-heart', 0.795926, 0.049896, 0.0645, 0.007953, 18.64);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'statlog-image', 0.967403, 0.010826, 0.35438, 0.03814, 69.8);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'statlog-vehicle', 0.729651, 0.03218, 0.29036, 0.024589, 93.44);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'synthetic-control', 0.922333, 0.030342, 0.17098, 0.019401, 35.32);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'tic-tac-toe', 0.983295, 0.007889, 0.07022, 0.007588, 3.0);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'vertebral-column-2clases', 0.84871, 0.047834, 0.02314, 0.006512, 10.32);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'wine', 0.979143, 0.020263, 0.00792, 0.002115, 4.32);
insert into results(norm, date, time, type, classifier, dataset, accuracy, accuracy_std, time_spent, time_spent_std, nodes) values(1, '2021-04-09', '23:43:20', 'crossval', 'j48svm', 'zoo', 0.92381, 0.046715, 0.09676, 0.012512, 14.48);

49
results/normalizados/stree.sql Normal file
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@@ -0,0 +1,49 @@
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:02','crossval','0.9918399999999999','0.010791403986507048','balance-scale','stree','1','0','0.01564922332763672','0.001228058544548453','{"C": 10000.0, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}','7.0','4.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:02','crossval','0.6066666666666667','0.30688398097290415','balloons','stree','1','0','0.0009676647186279296','0.0002367881119400382','{"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}','3.04','2.02','2.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:02','crossval','0.9481586710138177','0.017762307552983747','breast-cancer-wisc-diag','stree','1','0','0.002857346534729004','0.00019842965791362592','{"C": 0.2, "max_iter": 10000.0}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:03','crossval','0.7657051282051281','0.06922023305390425','breast-cancer-wisc-prog','stree','1','0','0.002074685096740723','0.0004066224889716958','{"C": 0.2, "max_iter": 10000.0}','2.56','1.78','1.78');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:03','crossval','0.9656628982528263','0.012882720775961002','breast-cancer-wisc','stree','1','0','0.0034239959716796877','0.0004755211146145311','{}','3.92','2.46','2.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:04','crossval','0.7255051421657592','0.04596424345908255','breast-cancer','stree','1','0','0.006020359992980957','0.001990502673664083','{}','9.52','5.26','4.04');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:17','crossval','0.6029189726594865','0.023230292245275567','cardiotocography-10clases','stree','1','0','0.25811831951141356','0.0314210294333643','{}','30.08','15.54','12.12');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:19','crossval','0.8842913007456503','0.01580017229575517','cardiotocography-3clases','stree','1','0','0.032402758598327634','0.0029452135541565977','{}','9.52','5.26','5.12');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:19','crossval','0.771602787456446','0.0587094228135243','conn-bench-sonar-mines-rocks','stree','1','0','0.008197841644287109','0.0014311584492272215','{}','5.44','3.22','2.84');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:20','crossval','0.6843613173424711','0.0403270755872992','cylinder-bands','stree','1','0','0.019214744567871093','0.0036259513257220024','{}','3.52','2.26','2.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:26','crossval','0.9652832284339133','0.01840681935790365','dermatology','stree','1','0','0.10673258781433105','0.011071385618113641','{"C": 55, "max_iter": 10000.0}','11.4','6.2','6.2');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:26','crossval','0.6716239316239316','0.08877112514663672','echocardiogram','stree','1','0','0.0010528135299682616','0.00012329582272334363','{"C": 7, "gamma": 0.1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:26','crossval','0.88','0.0547722557505166','fertility','stree','1','0','0.0009029483795166015','8.985260287819814e-05','{"C": 0.05, "max_features": "auto", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:27','crossval','0.7336805922792174','0.049766281568050116','haberman-survival','stree','1','0','0.004347615242004395','0.0008138944455178978','{}','6.48','3.74','3.28');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:27','crossval','0.7075043834015196','0.06988170032375486','heart-hungarian','stree','1','0','0.002285408973693848','0.00018612982992200836','{"C": 0.05, "max_iter": 10000.0}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:27','crossval','0.7877419354838711','0.07215718764924595','hepatitis','stree','1','0','0.002471780776977539','0.0005861380007886405','{"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}','2.48','1.74','1.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:27','crossval','0.7130518715001475','0.03723387507571413','ilpd-indian-liver','stree','1','0','0.0021682167053222656','0.0009278573484369175','{}','1.88','1.44','1.42');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:28','crossval','0.9302092555331992','0.0315040432760966','ionosphere','stree','1','0','0.007402029037475586','0.0007914535520963372','{"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}','3.2','2.1','2.1');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:28','crossval','0.9520000000000001','0.029933259094191526','iris','stree','1','0','0.0032801103591918947','0.0001681739375532264','{}','5.0','3.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:35','crossval','0.6995999999999999','0.02761955828756136','led-display','stree','1','0','0.1255587148666382','0.005677196093766789','{}','34.76','17.88','13.3');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:48','crossval','0.2536111111111111','0.03786448383119027','libras','stree','1','0','0.2506489419937134','0.018599137274566482','{"C": 0.08, "max_iter": 10000.0}','19.32','10.16','9.94');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:50','crossval','0.6894515958384763','0.043401193625496784','low-res-spect','stree','1','0','0.03629184246063232','0.0026942266748541423','{"C": 0.05, "max_iter": 10000.0}','9.52','5.26','5.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:50','crossval','0.759977011494253','0.09836735406434544','lymphography','stree','1','0','0.002750692367553711','0.0003574147020189625','{"C": 0.05, "max_iter": 10000.0}','3.36','2.18','2.18');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:51','crossval','0.805308182210708','0.024897168922554405','mammographic','stree','1','0','0.003717927932739258','0.0002334562471656256','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:51','crossval','0.7369264069264068','0.10707633598969517','molec-biol-promoter','stree','1','0','0.0019171428680419922','0.0002558217748088511','{"C": 0.05, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:52','crossval','0.565094298245614','0.04088778951436713','musk-1','stree','1','0','0.012906560897827149','0.0003487001831039861','{"C": 0.05, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:54','crossval','0.6696681013868963','0.02466397638475715','oocytes_merluccius_nucleus_4d','stree','1','0','0.036813783645629886','0.011420072913938121','{"C": 8.25, "gamma": 0.1, "kernel": "poly"}','2.16','1.58','1.58');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:56','crossval','0.9060664753706361','0.01947618443632987','oocytes_merluccius_states_2f','stree','1','0','0.03827941417694092','0.0022696202549713908','{}','6.04','3.52','3.52');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:57','crossval','0.7188584639404313','0.03644014184644201','oocytes_trisopterus_nucleus_2f','stree','1','0','0.017165846824645996','0.0031658347443004943','{}','3.6','2.3','2.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:58','crossval','0.8030703176604815','0.023544698695572304','oocytes_trisopterus_states_5b','stree','1','0','0.011374692916870117','0.0002904977551424975','{"C": 0.11, "max_iter": 10000.0}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:58','crossval','0.8543589743589743','0.04957147066090082','parkinsons','stree','1','0','0.0029172849655151366','0.000254502288407107','{}','3.04','2.02','2.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:58','crossval','0.7688659706306764','0.030512242922947463','pima','stree','1','0','0.004713902473449707','0.00036234890230219815','{}','3.16','2.08','2.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:59','crossval','0.7584848484848484','0.0954131508049414','pittsburg-bridges-MATERIAL','stree','1','0','0.002017765045166016','0.0007032473277629264','{"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}','2.28','1.64','1.64');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:59','crossval','0.6221904761904762','0.09159389814212923','pittsburg-bridges-REL-L','stree','1','0','0.005073995590209961','0.0015471340861317874','{}','6.24','3.62','3.5');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:32:59','crossval','0.5885964912280701','0.13116275959717713','pittsburg-bridges-SPAN','stree','1','0','0.0027930879592895507','0.0005646042707767776','{"C": 0.05, "max_iter": 10000.0}','4.08','2.54','2.54');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:00','crossval','0.8638095238095238','0.07623659318588133','pittsburg-bridges-T-OR-D','stree','1','0','0.0016234731674194336','0.00037310714376946114','{}','2.48','1.74','1.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:00','crossval','0.6332582582582582','0.07931272186851575','planning','stree','1','0','0.003254857063293457','0.00034353820348752235','{"C": 7, "gamma": 10.0, "kernel": "rbf", "max_iter": 10000.0}','4.24','2.62','2.62');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:00','crossval','0.711111111111111','0.07535922203472521','post-operative','stree','1','0','0.0011165428161621093','8.337944115351184e-05','{"C": 55, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:02','crossval','0.9499999999999998','0.03816957033781285','seeds','stree','1','0','0.03826602935791015','0.00878652443250852','{"C": 10000.0, "max_iter": 10000.0}','11.2','6.1','4.84');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:02','crossval','0.6782608695652174','0.03904983647915211','statlog-australian-credit','stree','1','0','0.0011624908447265625','0.00012125793010232072','{"C": 0.05, "max_features": "auto", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:04','crossval','0.7695000000000001','0.027771388153997628','statlog-german-credit','stree','1','0','0.017214603424072265','0.00353252091192701','{}','8.64','4.82','3.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:04','crossval','0.8425925925925926','0.039064857610609224','statlog-heart','stree','1','0','0.003080282211303711','8.908118032360401e-05','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:18','crossval','0.9134632034632034','0.014399975949955872','statlog-image','stree','1','0','0.28190260887145996','0.011044599418803204','{"C": 7, "max_iter": 10000.0}','17.76','9.38','8.44');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:20','crossval','0.7022721893491126','0.033859340958035986','statlog-vehicle','stree','1','0','0.03189016342163086','0.0035088938107595263','{}','13.36','7.18','5.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:27','crossval','0.9469999999999998','0.019983326383095815','synthetic-control','stree','1','0','0.13779988765716553','0.006975647611245406','{"C": 0.55, "max_iter": 10000.0}','11.28','6.14','6.14');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:28','crossval','0.6534505890052357','0.028021260679892277','tic-tac-toe','stree','1','0','0.013150224685668946','0.00026458604250187765','{"C": 0.2, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:28','crossval','0.8074193548387096','0.05185527767837077','vertebral-column-2clases','stree','1','0','0.0025788545608520508','0.00010979391980186945','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:29','crossval','0.9685555555555557','0.030594137669873376','wine','stree','1','0','0.0034023189544677736','0.00033841067192203703','{"C": 0.55, "max_iter": 10000.0}','5.0','3.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:33:29','crossval','0.877','0.06800461835723977','zoo','stree','1','0','0.005529937744140625','0.0006721646227264098','{"C": 0.1, "max_iter": 10000.0}','12.12','6.56','6.56');

55
results/normalizados/stree.txt Normal file
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* Process all datasets set with stree: tanveer norm: True std: False store in: stree
5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
Dataset Samp Var Cls Nodes Leaves Depth Accuracy Time Parameters
============================== ===== === === ======= ======= ======= =============== =============== ==========
balance-scale 625 4 3 7.00 4.00 3.00 0.991840±0.0108 0.015649±0.0012 {"C": 10000.0, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}
balloons 16 4 2 3.04 2.02 2.02 0.606667±0.3069 0.000968±0.0002 {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}
breast-cancer-wisc-diag 569 30 2 3.00 2.00 2.00 0.948159±0.0178 0.002857±0.0002 {"C": 0.2, "max_iter": 10000.0}
breast-cancer-wisc-prog 198 33 2 2.56 1.78 1.78 0.765705±0.0692 0.002075±0.0004 {"C": 0.2, "max_iter": 10000.0}
breast-cancer-wisc 699 9 2 3.92 2.46 2.46 0.965663±0.0129 0.003424±0.0005 {}
breast-cancer 286 9 2 9.52 5.26 4.04 0.725505±0.0460 0.006020±0.0020 {}
cardiotocography-10clases 2126 21 10 30.08 15.54 12.12 0.602919±0.0232 0.258118±0.0314 {}
cardiotocography-3clases 2126 21 3 9.52 5.26 5.12 0.884291±0.0158 0.032403±0.0029 {}
conn-bench-sonar-mines-rocks 208 60 2 5.44 3.22 2.84 0.771603±0.0587 0.008198±0.0014 {}
cylinder-bands 512 35 2 3.52 2.26 2.24 0.684361±0.0403 0.019215±0.0036 {}
dermatology 366 34 6 11.40 6.20 6.20 0.965283±0.0184 0.106733±0.0111 {"C": 55, "max_iter": 10000.0}
echocardiogram 131 10 2 1.00 1.00 1.00 0.671624±0.0888 0.001053±0.0001 {"C": 7, "gamma": 0.1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0}
fertility 100 9 2 1.00 1.00 1.00 0.880000±0.0548 0.000903±0.0001 {"C": 0.05, "max_features": "auto", "max_iter": 10000.0}
haberman-survival 306 3 2 6.48 3.74 3.28 0.733681±0.0498 0.004348±0.0008 {}
heart-hungarian 294 12 2 3.00 2.00 2.00 0.707504±0.0699 0.002285±0.0002 {"C": 0.05, "max_iter": 10000.0}
hepatitis 155 19 2 2.48 1.74 1.74 0.787742±0.0722 0.002472±0.0006 {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}
ilpd-indian-liver 583 9 2 1.88 1.44 1.42 0.713052±0.0372 0.002168±0.0009 {}
ionosphere 351 33 2 3.20 2.10 2.10 0.930209±0.0315 0.007402±0.0008 {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}
iris 150 4 3 5.00 3.00 3.00 0.952000±0.0299 0.003280±0.0002 {}
led-display 1000 7 10 34.76 17.88 13.30 0.699600±0.0276 0.125559±0.0057 {}
libras 360 90 15 19.32 10.16 9.94 0.253611±0.0379 0.250649±0.0186 {"C": 0.08, "max_iter": 10000.0}
low-res-spect 531 100 9 9.52 5.26 5.24 0.689452±0.0434 0.036292±0.0027 {"C": 0.05, "max_iter": 10000.0}
lymphography 148 18 4 3.36 2.18 2.18 0.759977±0.0984 0.002751±0.0004 {"C": 0.05, "max_iter": 10000.0}
mammographic 961 5 2 3.00 2.00 2.00 0.805308±0.0249 0.003718±0.0002 {}
molec-biol-promoter 106 57 2 3.00 2.00 2.00 0.736926±0.1071 0.001917±0.0003 {"C": 0.05, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}
musk-1 476 166 2 1.00 1.00 1.00 0.565094±0.0409 0.012907±0.0003 {"C": 0.05, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}
oocytes_merluccius_nucleus_4d 1022 41 2 2.16 1.58 1.58 0.669668±0.0247 0.036814±0.0114 {"C": 8.25, "gamma": 0.1, "kernel": "poly"}
oocytes_merluccius_states_2f 1022 25 3 6.04 3.52 3.52 0.906066±0.0195 0.038279±0.0023 {}
oocytes_trisopterus_nucleus_2f 912 25 2 3.60 2.30 2.24 0.718858±0.0364 0.017166±0.0032 {}
oocytes_trisopterus_states_5b 912 32 3 3.00 2.00 2.00 0.803070±0.0235 0.011375±0.0003 {"C": 0.11, "max_iter": 10000.0}
parkinsons 195 22 2 3.04 2.02 2.02 0.854359±0.0496 0.002917±0.0003 {}
pima 768 8 2 3.16 2.08 2.08 0.768866±0.0305 0.004714±0.0004 {}
pittsburg-bridges-MATERIAL 106 7 3 2.28 1.64 1.64 0.758485±0.0954 0.002018±0.0007 {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0}
pittsburg-bridges-REL-L 103 7 3 6.24 3.62 3.50 0.622190±0.0916 0.005074±0.0015 {}
pittsburg-bridges-SPAN 92 7 3 4.08 2.54 2.54 0.588596±0.1312 0.002793±0.0006 {"C": 0.05, "max_iter": 10000.0}
pittsburg-bridges-T-OR-D 102 7 2 2.48 1.74 1.74 0.863810±0.0762 0.001623±0.0004 {}
planning 182 12 2 4.24 2.62 2.62 0.633258±0.0793 0.003255±0.0003 {"C": 7, "gamma": 10.0, "kernel": "rbf", "max_iter": 10000.0}
post-operative 90 8 3 1.00 1.00 1.00 0.711111±0.0754 0.001117±0.0001 {"C": 55, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}
seeds 210 7 3 11.20 6.10 4.84 0.950000±0.0382 0.038266±0.0088 {"C": 10000.0, "max_iter": 10000.0}
statlog-australian-credit 690 14 2 1.00 1.00 1.00 0.678261±0.0390 0.001162±0.0001 {"C": 0.05, "max_features": "auto", "max_iter": 10000.0}
statlog-german-credit 1000 24 2 8.64 4.82 3.66 0.769500±0.0278 0.017215±0.0035 {}
statlog-heart 270 13 2 3.00 2.00 2.00 0.842593±0.0391 0.003080±0.0001 {}
statlog-image 2310 18 7 17.76 9.38 8.44 0.913463±0.0144 0.281903±0.0110 {"C": 7, "max_iter": 10000.0}
statlog-vehicle 846 18 4 13.36 7.18 5.66 0.702272±0.0339 0.031890±0.0035 {}
synthetic-control 600 60 6 11.28 6.14 6.14 0.947000±0.0200 0.137800±0.0070 {"C": 0.55, "max_iter": 10000.0}
tic-tac-toe 958 9 2 1.00 1.00 1.00 0.653451±0.0280 0.013150±0.0003 {"C": 0.2, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0}
vertebral-column-2clases 310 6 2 3.00 2.00 2.00 0.807419±0.0519 0.002579±0.0001 {}
wine 178 13 3 5.00 3.00 3.00 0.968556±0.0306 0.003402±0.0003 {"C": 0.55, "max_iter": 10000.0}
zoo 101 16 7 12.12 6.56 6.56 0.877000±0.0680 0.005530±0.0007 {"C": 0.1, "max_iter": 10000.0}
Time: 0h 1m 28s

49
results/normalizados/stree_default.sql Normal file
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replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:48','crossval','0.9078400000000001','0.027022479530938694','balance-scale','stree_default','1','0','0.014065136909484863','0.003356256194885882','{}','16.32','8.66','6.68');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:48','crossval','0.6416666666666666','0.27600825269465323','balloons','stree_default','1','0','0.0014453935623168945','0.00048784805125499193','{}','4.08','2.54','2.34');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:49','crossval','0.9666092221704703','0.016581312614548083','breast-cancer-wisc-diag','stree_default','1','0','0.004474539756774903','0.0005162784948413271','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:49','crossval','0.7908461538461538','0.06633460694762172','breast-cancer-wisc-prog','stree_default','1','0','0.004705686569213868','0.0005874887138947772','{}','3.44','2.22','2.22');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:49','crossval','0.9656628982528263','0.012882720775961002','breast-cancer-wisc','stree_default','1','0','0.003395237922668457','0.0004947719857876927','{}','3.92','2.46','2.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:34:49','crossval','0.7255051421657592','0.04596424345908255','breast-cancer','stree_default','1','0','0.006016244888305664','0.0019705691370880303','{}','9.52','5.26','4.04');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:02','crossval','0.6029189726594865','0.023230292245275567','cardiotocography-10clases','stree_default','1','0','0.2563737440109253','0.030549892954076986','{}','30.08','15.54','12.12');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:04','crossval','0.8842913007456503','0.01580017229575517','cardiotocography-3clases','stree_default','1','0','0.03261420249938965','0.0030456065966004155','{}','9.52','5.26','5.12');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:05','crossval','0.771602787456446','0.0587094228135243','conn-bench-sonar-mines-rocks','stree_default','1','0','0.008208627700805665','0.0014543365229276186','{}','5.44','3.22','2.84');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:06','crossval','0.6843613173424711','0.0403270755872992','cylinder-bands','stree_default','1','0','0.019361248016357423','0.0036520455327941543','{}','3.52','2.26','2.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:07','crossval','0.9704627915586821','0.016521621206752043','dermatology','stree_default','1','0','0.01973677635192871','0.001430262224385611','{}','11.0','6.0','6.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:07','crossval','0.8490883190883189','0.0650355715837188','echocardiogram','stree_default','1','0','0.002098259925842285','0.0002801813495844156','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:07','crossval','0.88','0.0547722557505166','fertility','stree_default','1','0','0.0010959434509277344','0.00010282517673575151','{}','1.0','1.0','1.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:07','crossval','0.7336805922792174','0.049766281568050116','haberman-survival','stree_default','1','0','0.004379959106445313','0.0007666798954801904','{}','6.48','3.74','3.28');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:07','crossval','0.8282232612507304','0.04871940627905826','heart-hungarian','stree_default','1','0','0.004726200103759765','0.0005667095613275619','{}','4.36','2.68','2.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:08','crossval','0.7980645161290322','0.07378851575436417','hepatitis','stree_default','1','0','0.0035898303985595703','0.0008488643081805688','{}','4.64','2.82','2.64');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:08','crossval','0.7130518715001475','0.03723387507571413','ilpd-indian-liver','stree_default','1','0','0.0021433162689208983','0.0009167842284522654','{}','1.88','1.44','1.42');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:09','crossval','0.8846197183098593','0.03695714618235266','ionosphere','stree_default','1','0','0.024134411811828613','0.004866466374706728','{}','6.04','3.52','3.52');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:09','crossval','0.9520000000000001','0.029933259094191526','iris','stree_default','1','0','0.0033076858520507814','0.00029582688362781513','{}','5.0','3.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:35:16','crossval','0.6995999999999999','0.02761955828756136','led-display','stree_default','1','0','0.12607113838195802','0.005472823185785991','{}','34.76','17.88','13.3');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:37:56','crossval','0.6980555555555555','0.05851888478553918','libras','stree_default','1','0','3.2097356271743775','0.43909148547322907','{}','74.8','37.9','28.46');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:05','crossval','0.85102274731088','0.036115696547377084','low-res-spect','stree_default','1','0','0.1774393081665039','0.012323526018892136','{}','16.2','8.6','8.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:06','crossval','0.8472643678160919','0.060229288406275214','lymphography','stree_default','1','0','0.004910616874694824','0.0004481332429668406','{}','5.12','3.06','3.06');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:06','crossval','0.805308182210708','0.024897168922554405','mammographic','stree_default','1','0','0.0038238859176635744','0.0005213750640919884','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:06','crossval','0.7764502164502166','0.08351281060668775','molec-biol-promoter','stree_default','1','0','0.0025696802139282228','0.0001947309808086681','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:09','crossval','0.8176666666666668','0.03328145229619156','musk-1','stree_default','1','0','0.0647481346130371','0.009914213318021168','{}','3.68','2.34','2.34');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:12','crossval','0.7273825920612147','0.02528451350172609','oocytes_merluccius_nucleus_4d','stree_default','1','0','0.044887299537658694','0.012174511752956753','{}','5.52','3.26','2.92');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:14','crossval','0.9060664753706361','0.01947618443632987','oocytes_merluccius_states_2f','stree_default','1','0','0.03846145153045654','0.0021951081957765728','{}','6.04','3.52','3.52');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:14','crossval','0.7188584639404313','0.03644014184644201','oocytes_trisopterus_nucleus_2f','stree_default','1','0','0.017146553993225098','0.0032112272582977305','{}','3.6','2.3','2.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:17','crossval','0.8663327928901701','0.019963031818889542','oocytes_trisopterus_states_5b','stree_default','1','0','0.04839353084564209','0.004813875208843272','{}','3.08','2.04','2.04');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:17','crossval','0.8543589743589743','0.04957147066090082','parkinsons','stree_default','1','0','0.00293088436126709','0.00023454434469966087','{}','3.04','2.02','2.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:17','crossval','0.7688659706306764','0.030512242922947463','pima','stree_default','1','0','0.004739713668823242','0.00037445991977090354','{}','3.16','2.08','2.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:18','crossval','0.8628571428571427','0.07236919683323605','pittsburg-bridges-MATERIAL','stree_default','1','0','0.0037888479232788086','0.0005896370405092044','{}','4.48','2.74','2.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:18','crossval','0.6221904761904762','0.09159389814212923','pittsburg-bridges-REL-L','stree_default','1','0','0.0051055288314819335','0.0016710560826529023','{}','6.24','3.62','3.5');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:18','crossval','0.6707017543859649','0.08917867889965793','pittsburg-bridges-SPAN','stree_default','1','0','0.005823330879211426','0.0013286817122288473','{}','7.44','4.22','4.1');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:18','crossval','0.8638095238095238','0.07623659318588133','pittsburg-bridges-T-OR-D','stree_default','1','0','0.001626429557800293','0.0003492996023521205','{}','2.48','1.74','1.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:19','crossval','0.7138138138138139','0.07202043946309418','planning','stree_default','1','0','0.0016888856887817382','0.0004383059592913558','{}','1.16','1.08','1.08');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:19','crossval','0.691111111111111','0.07630348761506396','post-operative','stree_default','1','0','0.0023808193206787107','0.0011270186597491917','{}','2.92','1.96','1.96');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:19','crossval','0.928095238095238','0.041918287860346314','seeds','stree_default','1','0','0.004807629585266113','0.00026429551359908953','{}','5.0','3.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:19','crossval','0.6781159420289855','0.038917563767356014','statlog-australian-credit','stree_default','1','0','0.001938614845275879','0.0002762651374347175','{}','1.04','1.02','1.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:20','crossval','0.7695000000000001','0.027771388153997628','statlog-german-credit','stree_default','1','0','0.017238106727600098','0.0034538756976054017','{}','8.64','4.82','3.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:20','crossval','0.8425925925925926','0.039064857610609224','statlog-heart','stree_default','1','0','0.003095235824584961','0.00023447586536594583','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:25','crossval','0.86991341991342','0.016262600654772162','statlog-image','stree_default','1','0','0.09091208934783936','0.003672333020016789','{}','15.72','8.36','7.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:27','crossval','0.7022721893491126','0.033859340958035986','statlog-vehicle','stree_default','1','0','0.03200491905212402','0.0035948874525991064','{}','13.36','7.18','5.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:37','crossval','0.9553333333333335','0.018009256878986794','synthetic-control','stree_default','1','0','0.2033984375','0.013455634798339165','{}','11.8','6.4','6.36');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:37','crossval','0.983296247818499','0.008356787795559038','tic-tac-toe','stree_default','1','0','0.00591310977935791','0.0004437194561528769','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:37','crossval','0.8074193548387096','0.05185527767837077','vertebral-column-2clases','stree_default','1','0','0.0025585460662841796','8.885090446324012e-05','{}','3.0','2.0','2.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:38','crossval','0.9741746031746031','0.02684380414757996','wine','stree_default','1','0','0.0036084318161010744','0.00035897396435915694','{}','5.0','3.0','3.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:38:38','crossval','0.9574761904761904','0.046554797887534714','zoo','stree_default','1','0','0.006736030578613281','0.0004044812194375824','{}','13.88','7.44','7.44');

55
results/normalizados/stree_default.txt Normal file
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* Process all datasets set with stree_default: tanveer norm: True std: False store in: stree_default
5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
Dataset Samp Var Cls Nodes Leaves Depth Accuracy Time Parameters
============================== ===== === === ======= ======= ======= =============== =============== ==========
balance-scale 625 4 3 16.32 8.66 6.68 0.907840±0.0270 0.014065±0.0034 {}
balloons 16 4 2 4.08 2.54 2.34 0.641667±0.2760 0.001445±0.0005 {}
breast-cancer-wisc-diag 569 30 2 3.00 2.00 2.00 0.966609±0.0166 0.004475±0.0005 {}
breast-cancer-wisc-prog 198 33 2 3.44 2.22 2.22 0.790846±0.0663 0.004706±0.0006 {}
breast-cancer-wisc 699 9 2 3.92 2.46 2.46 0.965663±0.0129 0.003395±0.0005 {}
breast-cancer 286 9 2 9.52 5.26 4.04 0.725505±0.0460 0.006016±0.0020 {}
cardiotocography-10clases 2126 21 10 30.08 15.54 12.12 0.602919±0.0232 0.256374±0.0305 {}
cardiotocography-3clases 2126 21 3 9.52 5.26 5.12 0.884291±0.0158 0.032614±0.0030 {}
conn-bench-sonar-mines-rocks 208 60 2 5.44 3.22 2.84 0.771603±0.0587 0.008209±0.0015 {}
cylinder-bands 512 35 2 3.52 2.26 2.24 0.684361±0.0403 0.019361±0.0037 {}
dermatology 366 34 6 11.00 6.00 6.00 0.970463±0.0165 0.019737±0.0014 {}
echocardiogram 131 10 2 3.00 2.00 2.00 0.849088±0.0650 0.002098±0.0003 {}
fertility 100 9 2 1.00 1.00 1.00 0.880000±0.0548 0.001096±0.0001 {}
haberman-survival 306 3 2 6.48 3.74 3.28 0.733681±0.0498 0.004380±0.0008 {}
heart-hungarian 294 12 2 4.36 2.68 2.66 0.828223±0.0487 0.004726±0.0006 {}
hepatitis 155 19 2 4.64 2.82 2.64 0.798065±0.0738 0.003590±0.0008 {}
ilpd-indian-liver 583 9 2 1.88 1.44 1.42 0.713052±0.0372 0.002143±0.0009 {}
ionosphere 351 33 2 6.04 3.52 3.52 0.884620±0.0370 0.024134±0.0049 {}
iris 150 4 3 5.00 3.00 3.00 0.952000±0.0299 0.003308±0.0003 {}
led-display 1000 7 10 34.76 17.88 13.30 0.699600±0.0276 0.126071±0.0055 {}
libras 360 90 15 74.80 37.90 28.46 0.698056±0.0585 3.209736±0.4391 {}
low-res-spect 531 100 9 16.20 8.60 8.08 0.851023±0.0361 0.177439±0.0123 {}
lymphography 148 18 4 5.12 3.06 3.06 0.847264±0.0602 0.004911±0.0004 {}
mammographic 961 5 2 3.00 2.00 2.00 0.805308±0.0249 0.003824±0.0005 {}
molec-biol-promoter 106 57 2 3.00 2.00 2.00 0.776450±0.0835 0.002570±0.0002 {}
musk-1 476 166 2 3.68 2.34 2.34 0.817667±0.0333 0.064748±0.0099 {}
oocytes_merluccius_nucleus_4d 1022 41 2 5.52 3.26 2.92 0.727383±0.0253 0.044887±0.0122 {}
oocytes_merluccius_states_2f 1022 25 3 6.04 3.52 3.52 0.906066±0.0195 0.038461±0.0022 {}
oocytes_trisopterus_nucleus_2f 912 25 2 3.60 2.30 2.24 0.718858±0.0364 0.017147±0.0032 {}
oocytes_trisopterus_states_5b 912 32 3 3.08 2.04 2.04 0.866333±0.0200 0.048394±0.0048 {}
parkinsons 195 22 2 3.04 2.02 2.02 0.854359±0.0496 0.002931±0.0002 {}
pima 768 8 2 3.16 2.08 2.08 0.768866±0.0305 0.004740±0.0004 {}
pittsburg-bridges-MATERIAL 106 7 3 4.48 2.74 2.74 0.862857±0.0724 0.003789±0.0006 {}
pittsburg-bridges-REL-L 103 7 3 6.24 3.62 3.50 0.622190±0.0916 0.005106±0.0017 {}
pittsburg-bridges-SPAN 92 7 3 7.44 4.22 4.10 0.670702±0.0892 0.005823±0.0013 {}
pittsburg-bridges-T-OR-D 102 7 2 2.48 1.74 1.74 0.863810±0.0762 0.001626±0.0003 {}
planning 182 12 2 1.16 1.08 1.08 0.713814±0.0720 0.001689±0.0004 {}
post-operative 90 8 3 2.92 1.96 1.96 0.691111±0.0763 0.002381±0.0011 {}
seeds 210 7 3 5.00 3.00 3.00 0.928095±0.0419 0.004808±0.0003 {}
statlog-australian-credit 690 14 2 1.04 1.02 1.02 0.678116±0.0389 0.001939±0.0003 {}
statlog-german-credit 1000 24 2 8.64 4.82 3.66 0.769500±0.0278 0.017238±0.0035 {}
statlog-heart 270 13 2 3.00 2.00 2.00 0.842593±0.0391 0.003095±0.0002 {}
statlog-image 2310 18 7 15.72 8.36 7.88 0.869913±0.0163 0.090912±0.0037 {}
statlog-vehicle 846 18 4 13.36 7.18 5.66 0.702272±0.0339 0.032005±0.0036 {}
synthetic-control 600 60 6 11.80 6.40 6.36 0.955333±0.0180 0.203398±0.0135 {}
tic-tac-toe 958 9 2 3.00 2.00 2.00 0.983296±0.0084 0.005913±0.0004 {}
vertebral-column-2clases 310 6 2 3.00 2.00 2.00 0.807419±0.0519 0.002559±0.0001 {}
wine 178 13 3 5.00 3.00 3.00 0.974175±0.0268 0.003608±0.0004 {}
zoo 101 16 7 13.88 7.44 7.44 0.957476±0.0466 0.006736±0.0004 {}
Time: 0h 3m 50s

49
results/normalizados/wodt.sql Normal file
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replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:13:53','crossval','0.9105599999999999','0.030929700936155203','balance-scale','wodt','1','0','0.21324075222015382','0.022901207386101848','{}','83.32','42.16','12.84');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:13:54','crossval','0.6266666666666667','0.23407026485414348','balloons','wodt','1','0','0.006847372055053711','0.002903877826101847','{}','6.28','3.64','3.62');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:14:00','crossval','0.9567706877814003','0.016914230172549206','breast-cancer-wisc-diag','wodt','1','0','0.12148640155792237','0.01934258481327128','{}','25.12','13.06','7.76');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:14:05','crossval','0.6870769230769231','0.06463654008582861','breast-cancer-wisc-prog','wodt','1','0','0.10070056438446046','0.009297048503327857','{}','41.16','21.08','9.26');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:14:12','crossval','0.9495077081192188','0.01703739203824271','breast-cancer-wisc','wodt','1','0','0.1322394847869873','0.017212358772069145','{}','36.8','18.9','9.74');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:14:27','crossval','0.6554325468844524','0.05487233490223692','breast-cancer','wodt','1','0','0.2974639749526978','0.02829323609286599','{}','421.76','211.38','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:16:26','crossval','0.7500512565589617','0.023847918777948455','cardiotocography-10clases','wodt','1','0','2.374505958557129','0.09044907986312886','{}','999.16','500.08','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:17:32','crossval','0.9022580502623583','0.01682397786753013','cardiotocography-3clases','wodt','1','0','1.2965420722961425','0.10332802112995174','{}','585.88','293.44','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:17:36','crossval','0.7971544715447153','0.05716696020561157','conn-bench-sonar-mines-rocks','wodt','1','0','0.08178516387939454','0.01793983528471189','{}','22.6','11.8','6.98');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:17:54','crossval','0.6945402627070247','0.03413508137216515','cylinder-bands','wodt','1','0','0.36812313079833986','0.023456447314929074','{}','101.16','51.08','13.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:17:59','crossval','0.95870788596816','0.02267092716846112','dermatology','wodt','1','0','0.08558360576629638','0.009163030020141403','{}','18.68','9.84','7.56');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:18:03','crossval','0.7328774928774928','0.0706950306289071','echocardiogram','wodt','1','0','0.07621054649353028','0.010653465843640943','{}','35.08','18.04','10.82');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:18:05','crossval','0.8019999999999999','0.0720832851637604','fertility','wodt','1','0','0.052550797462463376','0.009865634043983385','{}','79.16','40.08','35.56');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:18:26','crossval','0.6616869381279745','0.06504078462800772','haberman-survival','wodt','1','0','0.4164604330062866','0.03465050330440698','{}','476.76','238.88','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:18:36','crossval','0.7482758620689656','0.04934172609981429','heart-hungarian','wodt','1','0','0.20049129486083983','0.023078445752833795','{}','73.4','37.2','12.3');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:18:39','crossval','0.7877419354838708','0.08657910676004532','hepatitis','wodt','1','0','0.051876163482666014','0.006903293617037604','{}','22.68','11.84','6.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:19:16','crossval','0.6715517241379311','0.04266963563291409','ilpd-indian-liver','wodt','1','0','0.7394672966003418','0.04079052300663627','{}','647.04','324.02','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:19:23','crossval','0.8881086519114689','0.03764527302298102','ionosphere','wodt','1','0','0.1414583683013916','0.017158020866605343','{}','32.56','16.78','10.42');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:19:26','crossval','0.944','0.03555277766926235','iris','wodt','1','0','0.04254323959350586','0.0085627389063986','{}','16.6','8.8','7.38');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:20:57','crossval','0.7014999999999999','0.029584624384974015','led-display','wodt','1','0','1.7910533094406127','0.04404600358780579','{}','4097.88','2049.44','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:21:15','crossval','0.7761111111111112','0.05201495511442412','libras','wodt','1','0','0.3663883113861084','0.021033614938297272','{}','131.72','66.36','12.58');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:21:32','crossval','0.8570410862281785','0.03395969665674335','low-res-spect','wodt','1','0','0.3388829708099365','0.025404722162263967','{}','93.12','47.06','10.98');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:21:35','crossval','0.809448275862069','0.08117100751718888','lymphography','wodt','1','0','0.05676698684692383','0.007699755790549307','{}','22.24','11.62','7.34');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:22:33','crossval','0.7806417314335059','0.023703496492134483','mammographic','wodt','1','0','1.132075505256653','0.07506506634511496','{}','2107.8','1054.4','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:22:33','crossval','0.8019913419913419','0.08390146472090296','molec-biol-promoter','wodt','1','0','0.014979376792907714','0.0037749224410426807','{}','6.44','3.72','3.3');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:22:45','crossval','0.8418048245614035','0.03894767594364527','musk-1','wodt','1','0','0.21523403644561767','0.014357181162113004','{}','55.04','28.02','9.7');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:23:39','crossval','0.7143758967001433','0.031167138044523302','oocytes_merluccius_nucleus_4d','wodt','1','0','1.077880754470825','0.048071859340309914','{}','370.0','185.5','19.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:24:02','crossval','0.8991190817790531','0.018392253684405998','oocytes_merluccius_states_2f','wodt','1','0','0.45797646045684814','0.031076144718348856','{}','122.72','61.86','14.18');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:24:49','crossval','0.7302618146880442','0.029528774344107375','oocytes_trisopterus_nucleus_2f','wodt','1','0','0.9343574523925782','0.04572818300741046','{}','296.64','148.82','20.32');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:25:21','crossval','0.8775193658800216','0.024559755091526626','oocytes_trisopterus_states_5b','wodt','1','0','0.6305027294158936','0.042468646638130644','{}','154.44','77.72','16.4');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:25:24','crossval','0.901025641025641','0.04810956157075134','parkinsons','wodt','1','0','0.059291563034057616','0.01055478740684769','{}','22.16','11.58','8.5');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:25:59','crossval','0.698935574229692','0.03230807837032946','pima','wodt','1','0','0.6876588249206543','0.03466577583613701','{}','253.52','127.26','18.34');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:02','crossval','0.8175757575757575','0.07645815826535769','pittsburg-bridges-MATERIAL','wodt','1','0','0.06273589611053466','0.012351463710196854','{}','77.2','39.1','32.76');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:08','crossval','0.6077142857142858','0.10174727483578092','pittsburg-bridges-REL-L','wodt','1','0','0.1229737377166748','0.013397986454497272','{}','118.08','59.54','36.44');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:14','crossval','0.5921637426900584','0.09595142290915461','pittsburg-bridges-SPAN','wodt','1','0','0.11180374145507813','0.012817073494334351','{}','157.24','79.12','47.66');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:17','crossval','0.8324761904761904','0.061685987045133894','pittsburg-bridges-T-OR-D','wodt','1','0','0.05939210414886475','0.010921283462823625','{}','79.88','40.44','34.28');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:25','crossval','0.5642642642642642','0.0841539017305423','planning','wodt','1','0','0.172938551902771','0.022598157656707425','{}','77.76','39.38','14.24');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:33','crossval','0.5544444444444445','0.09328702554912162','post-operative','wodt','1','0','0.14343581199645997','0.021526588871244652','{}','362.16','181.58','50.0');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:26:36','crossval','0.9223809523809523','0.04359419129585074','seeds','wodt','1','0','0.06962965965270997','0.008967647298677685','{}','25.12','13.06','6.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:27:17','crossval','0.5624637681159421','0.041775597998254206','statlog-australian-credit','wodt','1','0','0.808171067237854','0.05310326177690986','{}','441.88','221.44','48.14');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:27:48','crossval','0.6877000000000001','0.03127634889177442','statlog-german-credit','wodt','1','0','0.611791033744812','0.03868067279916215','{}','198.88','99.94','16.42');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:27:54','crossval','0.7674074074074076','0.048454863530151965','statlog-heart','wodt','1','0','0.1247534704208374','0.010010913983272234','{}','48.56','24.78','9.7');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:28:54','crossval','0.9462770562770564','0.010028818503552679','statlog-image','wodt','1','0','1.1948295736312866','0.07319053510178329','{}','320.24','160.62','43.02');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:29:31','crossval','0.7055718760877131','0.035849202498875715','statlog-vehicle','wodt','1','0','0.7270735836029053','0.03821371885242998','{}','258.44','129.72','16.06');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:29:40','crossval','0.9500000000000002','0.019860625479688296','synthetic-control','wodt','1','0','0.16990867137908935','0.017103112034262763','{}','26.92','13.96','6.72');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:29:58','crossval','0.9180404668411868','0.026601040576775932','tic-tac-toe','wodt','1','0','0.3678532075881958','0.037207143935023695','{}','87.32','44.16','13.62');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:30:09','crossval','0.8019354838709677','0.05008213856793639','vertebral-column-2clases','wodt','1','0','0.21485376358032227','0.019045788752517546','{}','104.68','52.84','22.92');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:30:11','crossval','0.9719206349206349','0.029239495511339145','wine','wodt','1','0','0.02917142391204834','0.005861948918698455','{}','8.08','4.54','3.88');
replace into results (date,time,type,accuracy,accuracy_std,dataset,classifier,norm,stand,time_spent,time_spent_std,parameters,nodes,leaves,depth) values('2021-04-11','00:30:12','crossval','0.9393809523809523','0.051272271307097966','zoo','wodt','1','0','0.03375922203063965','0.00414028943244922','{}','16.52','8.76','6.0');

55
results/normalizados/wodt.txt Normal file
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* Process all datasets set with wodt: tanveer norm: True std: False store in: wodt
5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
Dataset Samp Var Cls Nodes Leaves Depth Accuracy Time Parameters
============================== ===== === === ======= ======= ======= =============== =============== ==========
balance-scale 625 4 3 83.32 42.16 12.84 0.910560±0.0309 0.213241±0.0229 {}
balloons 16 4 2 6.28 3.64 3.62 0.626667±0.2341 0.006847±0.0029 {}
breast-cancer-wisc-diag 569 30 2 25.12 13.06 7.76 0.956771±0.0169 0.121486±0.0193 {}
breast-cancer-wisc-prog 198 33 2 41.16 21.08 9.26 0.687077±0.0646 0.100701±0.0093 {}
breast-cancer-wisc 699 9 2 36.80 18.90 9.74 0.949508±0.0170 0.132239±0.0172 {}
breast-cancer 286 9 2 421.76 211.38 50.00 0.655433±0.0549 0.297464±0.0283 {}
cardiotocography-10clases 2126 21 10 999.16 500.08 50.00 0.750051±0.0238 2.374506±0.0904 {}
cardiotocography-3clases 2126 21 3 585.88 293.44 50.00 0.902258±0.0168 1.296542±0.1033 {}
conn-bench-sonar-mines-rocks 208 60 2 22.60 11.80 6.98 0.797154±0.0572 0.081785±0.0179 {}
cylinder-bands 512 35 2 101.16 51.08 13.00 0.694540±0.0341 0.368123±0.0235 {}
dermatology 366 34 6 18.68 9.84 7.56 0.958708±0.0227 0.085584±0.0092 {}
echocardiogram 131 10 2 35.08 18.04 10.82 0.732877±0.0707 0.076211±0.0107 {}
fertility 100 9 2 79.16 40.08 35.56 0.802000±0.0721 0.052551±0.0099 {}
haberman-survival 306 3 2 476.76 238.88 50.00 0.661687±0.0650 0.416460±0.0347 {}
heart-hungarian 294 12 2 73.40 37.20 12.30 0.748276±0.0493 0.200491±0.0231 {}
hepatitis 155 19 2 22.68 11.84 6.88 0.787742±0.0866 0.051876±0.0069 {}
ilpd-indian-liver 583 9 2 647.04 324.02 50.00 0.671552±0.0427 0.739467±0.0408 {}
ionosphere 351 33 2 32.56 16.78 10.42 0.888109±0.0376 0.141458±0.0172 {}
iris 150 4 3 16.60 8.80 7.38 0.944000±0.0356 0.042543±0.0086 {}
led-display 1000 7 10 4097.88 2049.44 50.00 0.701500±0.0296 1.791053±0.0440 {}
libras 360 90 15 131.72 66.36 12.58 0.776111±0.0520 0.366388±0.0210 {}
low-res-spect 531 100 9 93.12 47.06 10.98 0.857041±0.0340 0.338883±0.0254 {}
lymphography 148 18 4 22.24 11.62 7.34 0.809448±0.0812 0.056767±0.0077 {}
mammographic 961 5 2 2107.80 1054.40 50.00 0.780642±0.0237 1.132076±0.0751 {}
molec-biol-promoter 106 57 2 6.44 3.72 3.30 0.801991±0.0839 0.014979±0.0038 {}
musk-1 476 166 2 55.04 28.02 9.70 0.841805±0.0389 0.215234±0.0144 {}
oocytes_merluccius_nucleus_4d 1022 41 2 370.00 185.50 19.66 0.714376±0.0312 1.077881±0.0481 {}
oocytes_merluccius_states_2f 1022 25 3 122.72 61.86 14.18 0.899119±0.0184 0.457976±0.0311 {}
oocytes_trisopterus_nucleus_2f 912 25 2 296.64 148.82 20.32 0.730262±0.0295 0.934357±0.0457 {}
oocytes_trisopterus_states_5b 912 32 3 154.44 77.72 16.40 0.877519±0.0246 0.630503±0.0425 {}
parkinsons 195 22 2 22.16 11.58 8.50 0.901026±0.0481 0.059292±0.0106 {}
pima 768 8 2 253.52 127.26 18.34 0.698936±0.0323 0.687659±0.0347 {}
pittsburg-bridges-MATERIAL 106 7 3 77.20 39.10 32.76 0.817576±0.0765 0.062736±0.0124 {}
pittsburg-bridges-REL-L 103 7 3 118.08 59.54 36.44 0.607714±0.1017 0.122974±0.0134 {}
pittsburg-bridges-SPAN 92 7 3 157.24 79.12 47.66 0.592164±0.0960 0.111804±0.0128 {}
pittsburg-bridges-T-OR-D 102 7 2 79.88 40.44 34.28 0.832476±0.0617 0.059392±0.0109 {}
planning 182 12 2 77.76 39.38 14.24 0.564264±0.0842 0.172939±0.0226 {}
post-operative 90 8 3 362.16 181.58 50.00 0.554444±0.0933 0.143436±0.0215 {}
seeds 210 7 3 25.12 13.06 6.88 0.922381±0.0436 0.069630±0.0090 {}
statlog-australian-credit 690 14 2 441.88 221.44 48.14 0.562464±0.0418 0.808171±0.0531 {}
statlog-german-credit 1000 24 2 198.88 99.94 16.42 0.687700±0.0313 0.611791±0.0387 {}
statlog-heart 270 13 2 48.56 24.78 9.70 0.767407±0.0485 0.124753±0.0100 {}
statlog-image 2310 18 7 320.24 160.62 43.02 0.946277±0.0100 1.194830±0.0732 {}
statlog-vehicle 846 18 4 258.44 129.72 16.06 0.705572±0.0358 0.727074±0.0382 {}
synthetic-control 600 60 6 26.92 13.96 6.72 0.950000±0.0199 0.169909±0.0171 {}
tic-tac-toe 958 9 2 87.32 44.16 13.62 0.918040±0.0266 0.367853±0.0372 {}
vertebral-column-2clases 310 6 2 104.68 52.84 22.92 0.801935±0.0501 0.214854±0.0190 {}
wine 178 13 3 8.08 4.54 3.88 0.971921±0.0292 0.029171±0.0059 {}
zoo 101 16 7 16.52 8.76 6.00 0.939381±0.0513 0.033759±0.0041 {}
Time: 0h 16m 29s