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Add oc1 norm/no_norm results
This commit is contained in:
49
results/no_normalizados/oc1.sql
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49
results/no_normalizados/oc1.sql
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insert 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","13:43:28","crossval","0.919199988","0.022928468998468485","balance-scale","oc1","1","0","0.15758534","0.022345369377952624","{}","19.4","6.2","7.2");
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insert 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","13:43:28","crossval","0.619999972","0.2609071998773636","balloons","oc1","1","0","0.00030844","0.0002348338674597905","{}","2.2","1.0","2.2");
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insert 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","13:43:28","crossval","0.933477046","0.026311682939621855","breast-cancer-wisc-diag","oc1","1","0","0.4406648","0.06350629207104005","{}","8.0","3.0","4.4");
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insert 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","13:43:28","crossval","0.709999984","0.07955812149382789","breast-cancer-wisc-prog","oc1","1","0","0.16363574","0.036606637163787994","{}","11.4","4.2","5.8");
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insert 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","13:43:28","crossval","0.94019421","0.02100409938015746","breast-cancer-wisc","oc1","1","0","0.19944314","0.029906694694523308","{}","11.2","4.0","6.6");
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insert 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","13:43:28","crossval","0.64972776","0.06789902609753301","breast-cancer","oc1","1","0","0.09331238","0.01389738530376216","{}","23.0","6.4","8.4");
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insert 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","13:43:28","crossval","0.795527874","0.019194464349696225","cardiotocography-10clases","oc1","1","0","4.3503065","0.27225653156770274","{}","122.4","41.4","13.4");
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insert 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","13:43:28","crossval","0.899811318","0.016266190571653297","cardiotocography-3clases","oc1","1","0","2.42902948","0.40715254316028454","{}","52.4","18.0","10.2");
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insert 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","13:43:28","crossval","0.710798238","0.07164378928650933","conn-bench-sonar-mines-rocks","oc1","1","0","0.10360458","0.005299372073276266","{}","10.8","4.0","5.0");
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insert 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","13:43:28","crossval","0.671059568","0.04175041919191456","cylinder-bands","oc1","1","0","0.47492386000000003","0.08216321474793141","{}","36.8","12.6","9.8");
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insert 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","13:43:28","crossval","0.916086654","0.04339652757793572","dermatology","oc1","1","0","0.11251114","0.0159243193863592","{}","5.4","2.8","3.6");
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insert 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","13:43:28","crossval","0.74829059","0.086689318067258","echocardiogram","oc1","1","0","0.02473912","0.005133546359993653","{}","7.6","2.4","5.2");
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insert 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","13:43:28","crossval","0.793","0.08018473568413563","fertility","oc1","1","0","0.01644868","0.004574846246730538","{}","5.8","2.0","4.4");
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insert 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","13:43:28","crossval","0.651634068","0.05782825764577645","haberman-survival","oc1","1","0","0.0631877","0.0072805839422958605","{}","25.4","6.6","8.2");
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insert 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","13:43:28","crossval","0.758298106","0.04751287557647803","heart-hungarian","oc1","1","0","0.08981114","0.01770158774385703","{}","16.0","4.8","6.0");
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insert 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","13:43:28","crossval","0.756774218","0.07633927816039446","hepatitis","oc1","1","0","0.03985772","0.011435038445345543","{}","8.0","2.4","4.8");
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insert 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","13:43:28","crossval","0.66013908","0.050216248258669494","ilpd-indian-liver","oc1","1","0","0.30552824","0.029610812070800168","{}","38.6","11.4","10.0");
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insert 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","13:43:28","crossval","0.879742456","0.04078499717935586","ionosphere","oc1","1","0","0.2697913","0.03446318475946914","{}","8.6","2.4","6.0");
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insert 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","13:43:28","crossval","0.947999964","0.047217354202340585","iris","oc1","1","0","0.01697568","0.003151379752503623","{}","3.6","1.0","3.6");
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insert 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","13:43:28","crossval","0.6993","0.030572930537203204","led-display","oc1","1","0","0.29797592","0.012956706889562675","{}","62.6","23.4","8.2");
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insert 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","13:43:28","crossval","0.644999996","0.06212313913693778","libras","oc1","1","0","0.5830844","0.10705255659187753","{}","50.2","18.0","8.8");
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insert 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","13:43:28","crossval","0.824671134","0.034387913920443644","low-res-spect","oc1","1","0","1.21806182","0.1894391624213043","{}","32.2","11.4","7.4");
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insert 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","13:43:28","crossval","0.734633624","0.07505967701227854","lymphography","oc1","1","0","0.03662084","0.006085540069136117","{}","7.2","2.6","4.4");
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insert 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","13:43:28","crossval","0.768805056","0.042451008108027544","mammographic","oc1","1","0","0.40330064","0.0304541497247845","{}","84.0","21.2","12.6");
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insert 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","13:43:28","crossval","0.73480519","0.07929681982000171","molec-biol-promoter","oc1","1","0","0.00308648","0.00024732926413580575","{}","9.8","3.4","4.8");
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insert 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","13:43:28","crossval","0.77640132","0.04136666906353273","musk-1","oc1","1","0","0.75021326","0.05405970914733343","{}","28.8","9.4","11.6");
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insert 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","13:43:28","crossval","0.74319913","0.038637374982475575","oocytes_merluccius_nucleus_4d","oc1","1","0","1.4739426","0.20908235653650248","{}","70.2","21.4","11.8");
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insert 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","13:43:28","crossval","0.889223286","0.021904213371842132","oocytes_merluccius_states_2f","oc1","1","0","1.0546264","0.18662517073458842","{}","32.6","9.6","9.2");
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insert 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","13:43:28","crossval","0.747697088","0.03432152551574619","oocytes_trisopterus_nucleus_2f","oc1","1","0","1.0034749","0.10601749965660753","{}","52.8","15.6","11.8");
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insert 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","13:43:28","crossval","0.86392976","0.02062502994634808","oocytes_trisopterus_states_5b","oc1","1","0","1.3526446","0.20447791710418342","{}","38.4","13.0","12.0");
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insert 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","13:43:28","crossval","0.86564104","0.0549597058415768","parkinsons","oc1","1","0","0.0899414","0.01691889924773778","{}","6.2","2.4","4.0");
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insert 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","13:43:28","crossval","0.693026632","0.03464965512793265","pima","oc1","1","0","0.3920624","0.03647972198414917","{}","50.6","15.4","9.8");
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insert 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","13:43:28","crossval","0.8102597420000001","0.08791120411801688","pittsburg-bridges-MATERIAL","oc1","1","0","0.01630412","0.003393762619866039","{}","6.2","2.4","3.8");
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insert 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","13:43:28","crossval","0.604956518","0.12099535114803797","pittsburg-bridges-REL-L","oc1","1","0","0.0246469","0.0034962164987486755","{}","11.8","3.6","7.0");
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insert 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","13:43:28","crossval","0.579333326","0.096773599093883","pittsburg-bridges-SPAN","oc1","1","0","0.01922252","0.0027835986855954974","{}","11.8","4.0","5.6");
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insert 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","13:43:28","crossval","0.831545454","0.08260500811202823","pittsburg-bridges-T-OR-D","oc1","1","0","0.01537292","0.004610019216569803","{}","9.2","2.8","5.6");
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insert 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","13:43:28","crossval","0.5669882980000001","0.09819126087918144","planning","oc1","1","0","0.07031054","0.012096526938247818","{}","16.0","5.2","7.8");
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insert 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","13:43:28","crossval","0.542222202","0.1277555874609372","post-operative","oc1","1","0","0.01706538","0.004090332304698133","{}","13.8","4.0","6.0");
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insert 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","13:43:28","crossval","0.932380962","0.03674729708467471","seeds","oc1","1","0","0.03468252","0.003911751939257616","{}","4.8","2.2","3.6");
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insert 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","13:43:28","crossval","0.573913046","0.058026443678065934","statlog-australian-credit","oc1","1","0","0.41469248000000003","0.04788899725544737","{}","50.4","15.0","8.8");
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insert 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","13:43:28","crossval","0.6874","0.038028453364633716","statlog-german-credit","oc1","1","0","0.939049","0.1432174301094069","{}","62.4","18.0","13.4");
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insert 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","13:43:28","crossval","0.749259256","0.05822632907936435","statlog-heart","oc1","1","0","0.08672722","0.010369955067090184","{}","12.0","4.4","5.6");
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insert 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","13:43:28","crossval","0.950129852","0.009469844490506888","statlog-image","oc1","1","0","2.34150554","0.1429278477253342","{}","43.8","16.2","11.6");
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insert 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","13:43:28","crossval","0.70849635","0.03707889637712277","statlog-vehicle","oc1","1","0","0.85610944","0.06409603741808388","{}","62.0","18.6","11.8");
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insert 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","13:43:28","crossval","0.863166664","0.037233171992205105","synthetic-control","oc1","1","0","1.40889312","0.08426795206246342","{}","18.8","6.4","6.8");
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insert 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","13:43:28","crossval","0.918490308","0.03719306955411836","tic-tac-toe","oc1","1","0","0.3742426","0.06761291997684997","{}","20.4","7.2","8.2");
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insert 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","13:43:28","crossval","0.815161292","0.047132057674445754","vertebral-column-2clases","oc1","1","0","0.07522561999999999","0.00795117969399022","{}","14.0","4.0","6.0");
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insert 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","13:43:28","crossval","0.916165406","0.04659011245811016","wine","oc1","1","0","0.0363267","0.005601708344563382","{}","4.4","1.6","3.4");
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insert 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","13:43:28","crossval","0.890952386","0.07664919395809533","zoo","oc1","1","0","0.01431152","0.0020010060453355427","{}","6.4","2.8","3.8");
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108
results/no_normalizados/oc1.txt
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108
results/no_normalizados/oc1.txt
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Generating csv datasets
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========================
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Generating: balance-scale, balloons, breast-cancer-wisc-diag, breast-cancer-wisc-prog, breast-cancer-wisc, breast-cancer, cardiotocography-10clases, cardiotocography-3clases, conn-bench-sonar-mines-rocks, cylinder-bands, dermatology, echocardiogram, fertility, haberman-survival, heart-hungarian, hepatitis, ilpd-indian-liver, ionosphere, iris, led-display, libras, low-res-spect, lymphography, mammographic, molec-biol-promoter, musk-1, oocytes_merluccius_nucleus_4d, oocytes_merluccius_states_2f, oocytes_trisopterus_nucleus_2f, oocytes_trisopterus_states_5b, parkinsons, pima, pittsburg-bridges-MATERIAL, pittsburg-bridges-REL-L, pittsburg-bridges-SPAN, pittsburg-bridges-T-OR-D, planning, post-operative, seeds, statlog-australian-credit, statlog-german-credit,
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statlog-heart, statlog-image, statlog-vehicle, synthetic-control, tic-tac-toe, vertebral-column-2clases, wine, zoo, end
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Processing datasets
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===================
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*balance-scale : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*balloons : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*breast-cancer-wisc-diag : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*breast-cancer-wisc-prog : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*breast-cancer-wisc : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*breast-cancer : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*cardiotocography-10clases : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*cardiotocography-3clases : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*conn-bench-sonar-mines-rocks : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*cylinder-bands : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*dermatology : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*echocardiogram : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*fertility : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*haberman-survival : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*heart-hungarian : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*hepatitis : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*ilpd-indian-liver : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*ionosphere : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*iris : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*led-display : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*libras : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*low-res-spect : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*lymphography : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
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*mammographic : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*molec-biol-promoter : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*musk-1 : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*oocytes_merluccius_nucleus_4d : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*oocytes_merluccius_states_2f : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*oocytes_trisopterus_nucleus_2f: 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*oocytes_trisopterus_states_5b : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*parkinsons : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*pima : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*pittsburg-bridges-MATERIAL : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*pittsburg-bridges-REL-L : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*pittsburg-bridges-SPAN : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*pittsburg-bridges-T-OR-D : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*planning : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*post-operative : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*seeds : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*statlog-australian-credit : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*statlog-german-credit : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*statlog-heart : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*statlog-image : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*statlog-vehicle : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*synthetic-control : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*tic-tac-toe : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*vertebral-column-2clases : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*wine : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
*zoo : 57, 31, 1714, 17, 23, 79, 83, 97, 7, 1, done
|
||||
|
||||
Generating SQL
|
||||
==============
|
||||
Processing balance-scale nodes= 19.40 leaves= 6.20 depth= 7.20 accuracy=[0.919±0.023] time=[0.158±0.022] elements=[50 50]
|
||||
Processing balloons nodes= 2.20 leaves= 1.00 depth= 2.20 accuracy=[0.620±0.261] time=[0.000±0.000] elements=[50 50]
|
||||
Processing breast-cancer-wisc-diag nodes= 8.00 leaves= 3.00 depth= 4.40 accuracy=[0.933±0.026] time=[0.441±0.064] elements=[50 50]
|
||||
Processing breast-cancer-wisc-prog nodes= 11.40 leaves= 4.20 depth= 5.80 accuracy=[0.710±0.080] time=[0.164±0.037] elements=[50 50]
|
||||
Processing breast-cancer-wisc nodes= 11.20 leaves= 4.00 depth= 6.60 accuracy=[0.940±0.021] time=[0.199±0.030] elements=[50 50]
|
||||
Processing breast-cancer nodes= 23.00 leaves= 6.40 depth= 8.40 accuracy=[0.650±0.068] time=[0.093±0.014] elements=[50 50]
|
||||
Processing cardiotocography-10clases nodes=122.40 leaves= 41.40 depth=13.40 accuracy=[0.796±0.019] time=[4.350±0.272] elements=[50 50]
|
||||
Processing cardiotocography-3clases nodes= 52.40 leaves= 18.00 depth=10.20 accuracy=[0.900±0.016] time=[2.429±0.407] elements=[50 50]
|
||||
Processing conn-bench-sonar-mines-rocks nodes= 10.80 leaves= 4.00 depth= 5.00 accuracy=[0.711±0.072] time=[0.104±0.005] elements=[50 50]
|
||||
Processing cylinder-bands nodes= 36.80 leaves= 12.60 depth= 9.80 accuracy=[0.671±0.042] time=[0.475±0.082] elements=[50 50]
|
||||
Processing dermatology nodes= 5.40 leaves= 2.80 depth= 3.60 accuracy=[0.916±0.043] time=[0.113±0.016] elements=[50 50]
|
||||
Processing echocardiogram nodes= 7.60 leaves= 2.40 depth= 5.20 accuracy=[0.748±0.087] time=[0.025±0.005] elements=[50 50]
|
||||
Processing fertility nodes= 5.80 leaves= 2.00 depth= 4.40 accuracy=[0.793±0.080] time=[0.016±0.005] elements=[50 50]
|
||||
Processing haberman-survival nodes= 25.40 leaves= 6.60 depth= 8.20 accuracy=[0.652±0.058] time=[0.063±0.007] elements=[50 50]
|
||||
Processing heart-hungarian nodes= 16.00 leaves= 4.80 depth= 6.00 accuracy=[0.758±0.048] time=[0.090±0.018] elements=[50 50]
|
||||
Processing hepatitis nodes= 8.00 leaves= 2.40 depth= 4.80 accuracy=[0.757±0.076] time=[0.040±0.011] elements=[50 50]
|
||||
Processing ilpd-indian-liver nodes= 38.60 leaves= 11.40 depth=10.00 accuracy=[0.660±0.050] time=[0.306±0.030] elements=[50 50]
|
||||
Processing ionosphere nodes= 8.60 leaves= 2.40 depth= 6.00 accuracy=[0.880±0.041] time=[0.270±0.034] elements=[50 50]
|
||||
Processing iris nodes= 3.60 leaves= 1.00 depth= 3.60 accuracy=[0.948±0.047] time=[0.017±0.003] elements=[50 50]
|
||||
Processing led-display nodes= 62.60 leaves= 23.40 depth= 8.20 accuracy=[0.699±0.031] time=[0.298±0.013] elements=[50 50]
|
||||
Processing libras nodes= 50.20 leaves= 18.00 depth= 8.80 accuracy=[0.645±0.062] time=[0.583±0.107] elements=[50 50]
|
||||
Processing low-res-spect nodes= 32.20 leaves= 11.40 depth= 7.40 accuracy=[0.825±0.034] time=[1.218±0.189] elements=[50 50]
|
||||
Processing lymphography nodes= 7.20 leaves= 2.60 depth= 4.40 accuracy=[0.735±0.075] time=[0.037±0.006] elements=[50 50]
|
||||
Processing mammographic nodes= 84.00 leaves= 21.20 depth=12.60 accuracy=[0.769±0.042] time=[0.403±0.030] elements=[50 50]
|
||||
Processing molec-biol-promoter nodes= 9.80 leaves= 3.40 depth= 4.80 accuracy=[0.735±0.079] time=[0.003±0.000] elements=[50 50]
|
||||
Processing musk-1 nodes= 28.80 leaves= 9.40 depth=11.60 accuracy=[0.776±0.041] time=[0.750±0.054] elements=[50 50]
|
||||
Processing oocytes_merluccius_nucleus_4d nodes= 70.20 leaves= 21.40 depth=11.80 accuracy=[0.743±0.039] time=[1.474±0.209] elements=[50 50]
|
||||
Processing oocytes_merluccius_states_2f nodes= 32.60 leaves= 9.60 depth= 9.20 accuracy=[0.889±0.022] time=[1.055±0.187] elements=[50 50]
|
||||
Processing oocytes_trisopterus_nucleus_2f nodes= 52.80 leaves= 15.60 depth=11.80 accuracy=[0.748±0.034] time=[1.003±0.106] elements=[50 50]
|
||||
Processing oocytes_trisopterus_states_5b nodes= 38.40 leaves= 13.00 depth=12.00 accuracy=[0.864±0.021] time=[1.353±0.204] elements=[50 50]
|
||||
Processing parkinsons nodes= 6.20 leaves= 2.40 depth= 4.00 accuracy=[0.866±0.055] time=[0.090±0.017] elements=[50 50]
|
||||
Processing pima nodes= 50.60 leaves= 15.40 depth= 9.80 accuracy=[0.693±0.035] time=[0.392±0.036] elements=[50 50]
|
||||
Processing pittsburg-bridges-MATERIAL nodes= 6.20 leaves= 2.40 depth= 3.80 accuracy=[0.810±0.088] time=[0.016±0.003] elements=[50 50]
|
||||
Processing pittsburg-bridges-REL-L nodes= 11.80 leaves= 3.60 depth= 7.00 accuracy=[0.605±0.121] time=[0.025±0.003] elements=[50 50]
|
||||
Processing pittsburg-bridges-SPAN nodes= 11.80 leaves= 4.00 depth= 5.60 accuracy=[0.579±0.097] time=[0.019±0.003] elements=[50 50]
|
||||
Processing pittsburg-bridges-T-OR-D nodes= 9.20 leaves= 2.80 depth= 5.60 accuracy=[0.832±0.083] time=[0.015±0.005] elements=[50 50]
|
||||
Processing planning nodes= 16.00 leaves= 5.20 depth= 7.80 accuracy=[0.567±0.098] time=[0.070±0.012] elements=[50 50]
|
||||
Processing post-operative nodes= 13.80 leaves= 4.00 depth= 6.00 accuracy=[0.542±0.128] time=[0.017±0.004] elements=[50 50]
|
||||
Processing seeds nodes= 4.80 leaves= 2.20 depth= 3.60 accuracy=[0.932±0.037] time=[0.035±0.004] elements=[50 50]
|
||||
Processing statlog-australian-credit nodes= 50.40 leaves= 15.00 depth= 8.80 accuracy=[0.574±0.058] time=[0.415±0.048] elements=[50 50]
|
||||
Processing statlog-german-credit nodes= 62.40 leaves= 18.00 depth=13.40 accuracy=[0.687±0.038] time=[0.939±0.143] elements=[50 50]
|
||||
Processing statlog-heart nodes= 12.00 leaves= 4.40 depth= 5.60 accuracy=[0.749±0.058] time=[0.087±0.010] elements=[50 50]
|
||||
Processing statlog-image nodes= 43.80 leaves= 16.20 depth=11.60 accuracy=[0.950±0.009] time=[2.342±0.143] elements=[50 50]
|
||||
Processing statlog-vehicle nodes= 62.00 leaves= 18.60 depth=11.80 accuracy=[0.708±0.037] time=[0.856±0.064] elements=[50 50]
|
||||
Processing synthetic-control nodes= 18.80 leaves= 6.40 depth= 6.80 accuracy=[0.863±0.037] time=[1.409±0.084] elements=[50 50]
|
||||
Processing tic-tac-toe nodes= 20.40 leaves= 7.20 depth= 8.20 accuracy=[0.918±0.037] time=[0.374±0.068] elements=[50 50]
|
||||
Processing vertebral-column-2clases nodes= 14.00 leaves= 4.00 depth= 6.00 accuracy=[0.815±0.047] time=[0.075±0.008] elements=[50 50]
|
||||
Processing wine nodes= 4.40 leaves= 1.60 depth= 3.40 accuracy=[0.916±0.047] time=[0.036±0.006] elements=[50 50]
|
||||
Processing zoo nodes= 6.40 leaves= 2.80 depth= 3.80 accuracy=[0.891±0.077] time=[0.014±0.002] elements=[50 50]
|
||||
Reference in New Issue
Block a user