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stree_datasets/preliminary_results.txt
Ricardo Montañana 5611e5bc01 Commit Inicial
2020-11-20 11:23:40 +01:00

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Dataset Time(s) Score Depth Nodes
========== ======= ====== ===== =====
breast 0.04 0.9780 3 7
cardiotoc 1.24 0.9563 7 33
cod-rna 141.67 0.9426 2 3
connect4 541.73 0.7991 24 873
covtype 6158.29 0.6401 17 359
diabetes 0.18 0.6823 8 21
dna 0.94 0.9997 4 21
fourclass 0.08 0.7425 4 7
glass 0.08 0.4252 2 5 0.9860 con Stree(C=55, max_iter=7e5, random_state=1).fit(X, y).score(X, y) in 92.75 seconds
heart 0.03 0.8630 2 3
ijcnn1 21.82 0.9365 11 133
iris 0.02 0.9800 3 5
letter 148.59 0.1966 25 301 1.00 con Stree(C=57, kernel="poly", degree=5, random_state=1, max_iter=7e5, split_criteria="max_distance")
mnist 1101.62 1.0000 25 761
pendigits 13.99 0.9874 22 335
protein 60.23 0.8133 14 209
satimage 13.93 0.8340 18 141
segment 0.45 0.9615 15 43
shuttle 76.06 0.9758 11 93
usps 14.46 0.9998 16 117
vehicle 0.22 0.8593 11 39
wine 0.07 0.7978 4 7
{'C': 1.0, 'criterion': 'gini', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_depth': None, 'max_features': None, 'max_iter': 1000, 'min_samples_split': 0, 'random_state': 0, 'split_criteria': 'max_samples', 'splitter': 'random', 'tol': 0.0001}
***************************************************************************************
* 5 Fold Cross Validation *
***************************************************************************************
Score all csv files: normalize=False, standardize=False
Dataset Fit Time(s) Score Time(s) Score on Train Score on Test
========== ================== ================== ================== ==================
breast 0.75 (+/- 0.22) 0.00 (+/- 0.00) 0.99 (+/- 0.01) 0.96 (+/- 0.04)
cardiotoc 22.16 (+/- 6.33) 0.00 (+/- 0.00) 0.93 (+/- 0.07) 0.88 (+/- 0.12)
diabetes 8.01 (+/- 4.38) 0.00 (+/- 0.00) 0.75 (+/- 0.05) 0.74 (+/- 0.08)
dna 4.82 (+/- 0.96) 0.01 (+/- 0.00) 1.00 (+/- 0.00) 0.92 (+/- 0.03)
glass 7.85 (+/- 5.79) 0.00 (+/- 0.00) 0.65 (+/- 0.27) 0.46 (+/- 0.15)
heart 2.88 (+/- 1.65) 0.00 (+/- 0.00) 0.81 (+/- 0.26) 0.73 (+/- 0.19)
iris 0.28 (+/- 0.07) 0.00 (+/- 0.00) 0.98 (+/- 0.02) 0.97 (+/- 0.06)
wine 1.76 (+/- 0.71) 0.00 (+/- 0.00) 0.94 (+/- 0.22) 0.86 (+/- 0.16)
{'C': 17, 'criterion': 'gini', 'degree': 3, 'gamma': 0.6, 'kernel': 'linear', 'max_depth': None,
'max_features': None, 'max_iter': 100000.0, 'min_samples_split': 0, 'random_state': 0,
'split_criteria': 'max_distance', 'splitter': 'random', 'tol': 0.0001}
Dataset Time(s) Stree Time(s) D.Tree Time(s) SVC(L) Time(s) SVC(R) Time(s) SVC(P) Time(s) R.For. Time(s) Odte
========== ======== ====== ======== ====== ======== ====== ======== ====== ======== ====== ======== ====== ======== ======
breast 0.14 0.9795 0.00 1.0000 0.01 0.9722 0.01 0.9766 0.01 0.9795 0.19 1.0000 22.76 0.9824
cardiotoc 26.07 0.9976 0.01 0.9995 0.49 0.9346 0.23 0.7785 0.32 0.7808 0.30 0.9995 2505.96 0.9948
diabetes 10.05 0.7839 0.00 1.0000 0.03 0.5651 0.02 0.7682 0.02 0.7760 0.24 1.0000 1266.04 0.8255
dna 0.73 0.9997 0.04 0.9997 0.26 0.9799 1.95 0.9944 2.42 0.9997 0.51 0.9997 113.27 0.9997
glass 18.13 0.8271 0.00 1.0000 0.04 0.4579 0.00 0.3551 0.00 0.3551 0.20 1.0000 1358.97 0.8178
heart 2.40 0.8593 0.00 1.0000 0.01 0.8630 0.01 0.6630 0.00 0.7037 0.19 1.0000 284.16 0.9074
iris 0.03 0.9800 0.00 1.0000 0.01 0.9667 0.00 0.9733 0.00 0.9733 0.17 1.0000 5.09 0.9800
wine 1.75 0.9831 0.00 1.0000 0.02 0.8202 0.00 0.7079 0.00 0.6798 0.21 1.0000 118.26 1.0000
{'base_estimator__C': 1.0, 'base_estimator__criterion': 'gini', 'base_estimator__degree': 3, 'base_estimator__gamma': 'scale',
'base_estimator__kernel': 'linear', 'base_estimator__max_depth': None, 'base_estimator__max_features': None,
'base_estimator__max_iter': 100000.0, 'base_estimator__min_samples_split': 0, 'base_estimator__random_state': 0,
'base_estimator__split_criteria': 'impurity', 'base_estimator__splitter': 'random', 'base_estimator__tol': 0.0001,
'base_estimator': Stree(random_state=0), 'max_features': None, 'max_samples': None, 'n_estimators': 100,
'n_jobs': 1, 'random_state': 0}
Dataset Time(s) Stree Time(s) D.Tree Time(s) SVC(L) Time(s) SVC(R) Time(s) SVC(P) Time(s) R.For. Time(s) Odte
========== ======== ====== ======== ====== ======== ====== ======== ====== ======== ====== ======== ====== ======== ======
breast 4.93 0.9854 0.00 1.0000 0.01 0.9722 0.01 0.9766 0.01 0.9795 0.19 1.0000 10.14 0.9824
cardiotoc 101.51 0.9995 0.01 0.9995 0.51 0.9346 0.22 0.7785 0.31 0.7808 0.33 0.9995 714.00 0.9939
diabetes 81.34 0.7891 0.00 1.0000 0.03 0.5651 0.02 0.7682 0.02 0.7760 0.23 1.0000 500.23 0.8177
dna 22.59 0.9997 0.04 0.9997 0.26 0.9799 2.02 0.9944 2.27 0.9997 0.50 0.9997 27.65 0.9997
glass 95.31 0.9766 0.00 1.0000 0.04 0.4579 0.00 0.3551 0.00 0.3551 0.19 1.0000 605.05 0.8224
heart 25.36 0.8815 0.00 1.0000 0.01 0.8630 0.00 0.6630 0.00 0.7037 0.17 1.0000 103.53 0.9037
iris 0.97 0.9933 0.00 1.0000 0.01 0.9667 0.00 0.9733 0.00 0.9733 0.17 1.0000 2.23 0.9800
wine 4.52 1.0000 0.00 1.0000 0.02 0.8202 0.00 0.7079 0.00 0.6798 0.18 1.0000 42.17 0.9888
{'base_estimator__C': 1.0, 'base_estimator__criterion': 'gini', 'base_estimator__degree': 3, 'base_estimator__gamma': 'scale',
'base_estimator__kernel': 'linear', 'base_estimator__max_depth': None, 'base_estimator__max_features': None,
'base_estimator__max_iter': 100000.0, 'base_estimator__min_samples_split': 0, 'base_estimator__random_state': 1,
'base_estimator__split_criteria': 'impurity', 'base_estimator__splitter': 'random', 'base_estimator__tol': 0.0001,
'base_estimator': Stree(random_state=1), 'max_features': None, 'max_samples': None, 'n_estimators': 100, 'n_jobs': -1,
'random_state': 0}
**************************************************************************************************************************************************************************
* 5 Folds Cross Validation: all - 43 records -- stree in develop -- *
**************************************************************************************************************************************************************************
Dataset Date N S Fit Time (sec) Score Time (sec) Score on Train Score on Test Reference Parameters
============================== =================== = = ==================== ==================== ==================== ==================== ========= =====================
balance-scale 2020-11-12 00:58:16 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.9488 (+/- 0.05) 0.90463 + {"C": 10000.0, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
balloons 2020-11-12 00:58:16 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.8667 (+/- 0.53) 0.66250 + {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
breast-cancer 2020-11-12 00:58:17 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.7911 (+/- 0.03) 0.7309 (+/- 0.08) 0.73824 - {"C": 0.55, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0, "random_state": 1}
breast-cancer-wisc 2020-11-12 00:58:17 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9796 (+/- 0.01) 0.9657 (+/- 0.04) 0.97026 - {"C": 0.55, "max_iter": 10000.0, "random_state": 1}
breast-cancer-wisc-diag 2020-11-12 00:58:17 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.9895 (+/- 0.00) 0.9789 (+/- 0.01) 0.97435 + {"C": 0.2, "max_iter": 10000.0, "random_state": 1}
breast-cancer-wisc-prog 2020-11-12 00:58:17 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9116 (+/- 0.02) 0.8285 (+/- 0.05) 0.79934 + {"C": 0.2, "max_iter": 10000.0, "random_state": 1}
cardiotocography-10clases 2020-11-12 00:58:18 1 0 0.30 (+/- 0.04) 0.01 (+/- 0.00) 0.8195 (+/- 0.02) 0.6665 (+/- 0.06) 0.82776 - {"C": 0.05, "max_iter": 10000.0, "random_state": 1}
cardiotocography-3clases 2020-11-12 00:58:18 1 0 0.07 (+/- 0.02) 0.00 (+/- 0.00) 0.9193 (+/- 0.02) 0.8481 (+/- 0.13) 0.92013 - {"C": 0.05, "max_iter": 10000.0, "random_state": 1}
cylinder-bands 2020-11-12 00:58:18 1 0 0.48 (+/- 0.03) 0.00 (+/- 0.00) 0.7759 (+/- 0.02) 0.6327 (+/- 0.13) 0.76914 - {"C": 7, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
dermatology 2020-11-12 00:58:18 1 0 0.05 (+/- 0.02) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.9755 (+/- 0.05) 0.97328 + {"C": 55, "max_iter": 10000.0, "random_state": 1}
echocardiogram 2020-11-12 00:58:18 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.8931 (+/- 0.03) 0.8473 (+/- 0.05) 0.84853 - {"C": 55, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
fertility 2020-11-12 00:58:18 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.8800 (+/- 0.01) 0.8800 (+/- 0.05) 0.88400 - {"C": 0.05, "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
haberman-survival 2020-11-12 00:58:19 1 0 0.19 (+/- 0.16) 0.00 (+/- 0.00) 0.8113 (+/- 0.02) 0.7647 (+/- 0.03) 0.73925 + {"C": 10000.0, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_iter": 1000000.0, "random_state": 1}
heart-hungarian 2020-11-12 00:58:19 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.8742 (+/- 0.01) 0.8299 (+/- 0.05) 0.82047 + {"C": 0.05, "max_iter": 10000.0, "random_state": 1}
hepatitis 2020-11-12 00:58:19 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9387 (+/- 0.03) 0.8645 (+/- 0.14) 0.82320 + {"C": 0.05, "gamma": 1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
ilpd-indian-liver 2020-11-12 00:58:19 1 0 0.23 (+/- 0.27) 0.00 (+/- 0.00) 0.7663 (+/- 0.02) 0.7427 (+/- 0.05) 0.71503 + {"C": 7, "max_iter": 10000.0, "random_state": 1}
ionosphere 2020-11-12 00:58:19 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9964 (+/- 0.00) 0.9487 (+/- 0.06) 0.94422 + {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
iris 2020-11-12 00:58:19 0 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.9783 (+/- 0.02) 0.9800 (+/- 0.05) 0.97866 + {}
led-display 2020-11-12 01:09:29 1 0 613.49 (+/- 62.98) 0.00 (+/- 0.00) 0.7533 (+/- 0.02) 0.7120 (+/- 0.04) 0.71020 + {"C": 10000.0, "max_iter": 1000000.0, "random_state": 1}
lymphography 2020-11-12 01:09:29 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9273 (+/- 0.01) 0.8648 (+/- 0.09) 0.85540 + {"C": 0.05, "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
mammographic 2020-11-12 01:09:29 1 0 0.06 (+/- 0.03) 0.00 (+/- 0.00) 0.8463 (+/- 0.02) 0.8294 (+/- 0.07) 0.82747 + {"C": 0.05, "gamma": 1, "kernel": "poly", "max_iter": 10000.0, "random_state": 1}
oocytes_merluccius_nucleus_4d 2020-11-12 01:09:30 1 0 0.27 (+/- 0.05) 0.00 (+/- 0.00) 0.9440 (+/- 0.01) 0.8082 (+/- 0.06) 0.83996 - {"C": 7, "gamma": 0.1, "kernel": "poly", "random_state": 1}
oocytes_merluccius_states_2f 2020-11-12 01:09:30 1 0 0.04 (+/- 0.00) 0.00 (+/- 0.00) 0.9550 (+/- 0.02) 0.9119 (+/- 0.07) 0.92996 - {"C": 0.55, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0, "random_state": 1}
oocytes_trisopterus_nucleus_2f 2020-11-12 01:09:31 1 0 0.12 (+/- 0.03) 0.00 (+/- 0.00) 0.8438 (+/- 0.01) 0.7477 (+/- 0.12) 0.83333 - {"C": 0.2, "max_iter": 10000.0, "random_state": 1}
oocytes_trisopterus_states_5b 2020-11-12 01:09:31 1 0 0.03 (+/- 0.01) 0.00 (+/- 0.00) 0.9353 (+/- 0.01) 0.8454 (+/- 0.14) 0.93158 - {"C": 0.05, "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
parkinsons 2020-11-12 01:09:31 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.8782 (+/- 0.04) 0.8462 (+/- 0.15) 0.92022 - {"C": 0.55, "gamma": 0.1, "kernel": "rbf", "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
pima 2020-11-12 01:09:31 1 0 0.02 (+/- 0.00) 0.00 (+/- 0.00) 0.8057 (+/- 0.01) 0.7800 (+/- 0.05) 0.76719 + {"C": 0.55, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
pittsburg-bridges-MATERIAL 2020-11-12 01:09:31 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.9175 (+/- 0.05) 0.8861 (+/- 0.13) 0.86429 + {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
pittsburg-bridges-REL-L 2020-11-12 01:09:31 1 0 0.13 (+/- 0.07) 0.00 (+/- 0.00) 0.9468 (+/- 0.12) 0.6762 (+/- 0.35) 0.69593 - {"C": 10000.0, "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
pittsburg-bridges-SPAN 2020-11-12 01:09:31 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.8208 (+/- 0.07) 0.6772 (+/- 0.31) 0.68913 - {"C": 0.05, "max_iter": 10000.0, "random_state": 1}
pittsburg-bridges-T-OR-D 2020-11-12 01:09:32 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.9461 (+/- 0.03) 0.9024 (+/- 0.06) 0.87437 + {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
planning 2020-11-12 01:09:32 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.7255 (+/- 0.04) 0.72558 - {"C": 7, "gamma": 10.0, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
post-operative 2020-11-12 01:09:32 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.7639 (+/- 0.17) 0.7222 (+/- 0.00) 0.71174 + {"C": 55, "degree": 5, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
seeds 2020-11-12 01:09:32 1 0 0.02 (+/- 0.02) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.9619 (+/- 0.08) 0.95630 + {"C": 10000.0, "max_iter": 10000.0, "random_state": 1}
statlog-australian-credit 2020-11-12 01:09:32 1 0 0.02 (+/- 0.02) 0.00 (+/- 0.00) 0.6801 (+/- 0.01) 0.6797 (+/- 0.01) 0.67828 + {"C": 0.05, "gamma": 1, "kernel": "poly", "max_features": "auto", "max_iter": 10000.0, "random_state": 1}
statlog-german-credit 2020-11-12 01:15:02 1 0 230.23 (+/- 112.91) 0.00 (+/- 0.00) 0.8562 (+/- 0.03) 0.7620 (+/- 0.02) 0.75620 + {"C": 10000.0, "max_iter": 1000000.0, "random_state": 1}
statlog-heart 2020-11-12 01:15:03 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.8889 (+/- 0.03) 0.8481 (+/- 0.09) 0.84230 + {"C": 0.55, "max_iter": 10000.0, "random_state": 1}
statlog-image 2020-11-12 01:15:07 1 0 3.95 (+/- 0.38) 0.00 (+/- 0.00) 0.9761 (+/- 0.00) 0.9593 (+/- 0.02) 0.97619 - {"C": 7, "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
statlog-vehicle 2020-11-12 01:15:07 1 0 0.18 (+/- 0.03) 0.00 (+/- 0.00) 0.9001 (+/- 0.02) 0.8014 (+/- 0.01) 0.80067 + {"C": 0.55, "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
tic-tac-toe 2020-11-12 01:15:08 1 0 0.01 (+/- 0.00) 0.00 (+/- 0.00) 0.9911 (+/- 0.01) 0.9874 (+/- 0.05) 0.98538 + {"C": 0.2, "gamma": 0.1, "kernel": "poly", "max_iter": 10000.0, "random_state": 1}
vertebral-column-2clases 2020-11-12 01:15:08 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 0.8677 (+/- 0.06) 0.8290 (+/- 0.25) 0.84915 - {"C": 0.2, "max_iter": 10000.0, "random_state": 1}
wine 2020-11-12 01:15:08 1 0 0.00 (+/- 0.00) 0.00 (+/- 0.00) 1.0000 (+/- 0.00) 0.9778 (+/- 0.04) 0.99328 - {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000.0, "random_state": 1}
zoo 2020-11-12 01:15:08 1 0 0.04 (+/- 0.01) 0.00 (+/- 0.00) 0.9950 (+/- 0.01) 0.9705 (+/- 0.05) 0.96039 + {"C": 7, "max_features": "auto", "max_iter": 10000.0, "random_state": 1, "split_criteria": "max_samples"}
stree has better results 25 times
stree has worse results 18 times
stree has equal results 0 times
****************************************************************************************************************************************************
* Grid Searches done so far - 21 records -- bagging in galgo -- *
****************************************************************************************************************************************************
Dataset Date N S Fit Time (sec) Score Time (sec) Score on Train Score on Test Reference
============================== =================== = = ==================== ==================== ==================== ==================== =========
balloons 2020-11-11 11:41:47 1 1 0.81 (+/- 0.09) 0.11 (+/- 0.00) 0.7949 (+/- 0.14) 0.6833 (+/- 0.43) 0.66250 +
breast-cancer 2020-11-11 22:19:26 1 1 1.42 (+/- 0.15) 0.55 (+/- 0.10) 0.7824 (+/- 0.03) 0.7519 (+/- 0.06) 0.73824 +
breast-cancer-wisc 2020-11-12 04:10:14 1 1 0.78 (+/- 0.09) 0.26 (+/- 0.07) 0.9753 (+/- 0.01) 0.9771 (+/- 0.04) 0.97026 +
breast-cancer-wisc-diag 2020-11-12 02:21:22 1 1 0.66 (+/- 0.05) 0.13 (+/- 0.03) 0.9864 (+/- 0.01) 0.9807 (+/- 0.02) 0.97435 +
breast-cancer-wisc-prog 2020-11-11 23:10:52 1 1 1285.58 (+/- 173.05) 1.08 (+/- 0.27) 0.9912 (+/- 0.01) 0.8337 (+/- 0.07) 0.79934 +
echocardiogram 2020-11-12 02:28:43 1 1 1.30 (+/- 0.08) 0.28 (+/- 0.09) 0.8645 (+/- 0.02) 0.8621 (+/- 0.08) 0.84853 +
fertility 2020-11-11 23:12:48 1 1 0.48 (+/- 0.10) 0.18 (+/- 0.06) 0.9525 (+/- 0.03) 0.8900 (+/- 0.04) 0.88400 +
hepatitis 2020-11-12 04:18:51 1 1 0.50 (+/- 0.10) 0.18 (+/- 0.04) 1.0000 (+/- 0.00) 0.8645 (+/- 0.09) 0.82320 +
ionosphere 2020-11-14 05:39:40 1 1 33.82 (+/- 8.96) 0.94 (+/- 0.14) 0.9922 (+/- 0.01) 0.9600 (+/- 0.06) 0.94422 +
iris 2020-11-13 19:05:32 1 1 0.69 (+/- 0.08) 0.17 (+/- 0.10) 0.9817 (+/- 0.01) 0.9733 (+/- 0.03) 0.97866 -
lymphography 2020-11-13 22:15:16 1 1 4.82 (+/- 1.78) 0.83 (+/- 0.43) 0.9341 (+/- 0.01) 0.8851 (+/- 0.03) 0.85540 +
molec-biol-promoter 2020-11-13 19:39:34 1 1 45.73 (+/- 1.55) 0.33 (+/- 0.03) 1.0000 (+/- 0.00) 0.9152 (+/- 0.07) 0.81827 +
parkinsons 2020-11-13 17:30:13 1 1 0.84 (+/- 0.33) 0.20 (+/- 0.08) 0.8859 (+/- 0.04) 0.8615 (+/- 0.20) 0.92022 -
pittsburg-bridges-MATERIAL 2020-11-13 17:12:51 1 1 0.65 (+/- 0.09) 0.11 (+/- 0.01) 0.8726 (+/- 0.02) 0.8771 (+/- 0.08) 0.86429 +
pittsburg-bridges-REL-L 2020-11-14 01:53:54 1 1 1.58 (+/- 0.18) 0.22 (+/- 0.01) 0.7159 (+/- 0.06) 0.6957 (+/- 0.29) 0.69593 -
pittsburg-bridges-SPAN 2020-11-14 01:23:10 1 1 2.03 (+/- 0.23) 0.21 (+/- 0.01) 0.7828 (+/- 0.06) 0.6871 (+/- 0.27) 0.68913 -
pittsburg-bridges-T-OR-D 2020-11-13 21:53:35 1 1 0.76 (+/- 0.03) 0.11 (+/- 0.01) 0.8824 (+/- 0.02) 0.8829 (+/- 0.08) 0.87437 +
planning 2020-11-14 10:49:20 1 1 6.34 (+/- 0.54) 1.12 (+/- 0.33) 0.9986 (+/- 0.01) 0.7366 (+/- 0.08) 0.72558 +
post-operative 2020-11-14 01:18:58 1 1 0.33 (+/- 0.02) 0.11 (+/- 0.01) 0.7111 (+/- 0.01) 0.7111 (+/- 0.04) 0.71174 -
seeds 2020-11-14 09:00:27 1 1 112.55 (+/- 44.52) 0.58 (+/- 0.22) 0.9762 (+/- 0.01) 0.9667 (+/- 0.07) 0.95630 +
zoo 2020-11-13 20:20:29 1 1 20.81 (+/- 4.72) 0.73 (+/- 0.33) 0.9852 (+/- 0.02) 0.9700 (+/- 0.05) 0.96039 +
bagging has better results 16 times
bagging has worse results 5 times
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