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https://github.com/Doctorado-ML/Stree_datasets.git
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57 lines
7.7 KiB
Plaintext
57 lines
7.7 KiB
Plaintext
* Process all datasets set with stree_default: tanveer norm: False std: False discretize: False store in: stree_default
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5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
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Dataset Samp Var Cls Nodes Leaves Depth Accuracy Time Parameters
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============================== ===== === === ======= ======= ======= =============== =============== ============================================
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balance-scale 625 4 3 0.00 0.00 0.00 nan± nan 0.000570±0.0001 {"max_features": "sqrt", "splitter": "fcbf"}
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balloons 16 4 2 0.00 0.00 0.00 nan± nan 0.000503±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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breast-cancer-wisc-diag 569 30 2 0.00 0.00 0.00 nan± nan 0.000569±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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breast-cancer-wisc-prog 198 33 2 0.00 0.00 0.00 nan± nan 0.000528±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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breast-cancer-wisc 699 9 2 0.00 0.00 0.00 nan± nan 0.000556±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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breast-cancer 286 9 2 0.00 0.00 0.00 nan± nan 0.000527±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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cardiotocography-10clases 2126 21 10 0.00 0.00 0.00 nan± nan 0.000695±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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cardiotocography-3clases 2126 21 3 0.00 0.00 0.00 nan± nan 0.000667±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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conn-bench-sonar-mines-rocks 208 60 2 0.00 0.00 0.00 nan± nan 0.000539±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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cylinder-bands 512 35 2 0.00 0.00 0.00 nan± nan 0.000575±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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dermatology 366 34 6 0.00 0.00 0.00 nan± nan 0.000552±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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echocardiogram 131 10 2 0.00 0.00 0.00 nan± nan 0.000506±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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fertility 100 9 2 0.00 0.00 0.00 nan± nan 0.000502±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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haberman-survival 306 3 2 0.00 0.00 0.00 nan± nan 0.000526±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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heart-hungarian 294 12 2 0.00 0.00 0.00 nan± nan 0.000523±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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hepatitis 155 19 2 0.00 0.00 0.00 nan± nan 0.000511±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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ilpd-indian-liver 583 9 2 0.00 0.00 0.00 nan± nan 0.000542±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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ionosphere 351 33 2 0.00 0.00 0.00 nan± nan 0.000544±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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iris 150 4 3 0.00 0.00 0.00 nan± nan 0.000512±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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led-display 1000 7 10 0.00 0.00 0.00 nan± nan 0.000593±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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libras 360 90 15 0.00 0.00 0.00 nan± nan 0.000579±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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low-res-spect 531 100 9 0.00 0.00 0.00 nan± nan 0.000619±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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lymphography 148 18 4 0.00 0.00 0.00 nan± nan 0.000510±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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mammographic 961 5 2 0.00 0.00 0.00 nan± nan 0.000559±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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molec-biol-promoter 106 57 2 0.00 0.00 0.00 nan± nan 0.000512±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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musk-1 476 166 2 0.00 0.00 0.00 nan± nan 0.000641±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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oocytes_merluccius_nucleus_4d 1022 41 2 0.00 0.00 0.00 nan± nan 0.000621±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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oocytes_merluccius_states_2f 1022 25 3 0.00 0.00 0.00 nan± nan 0.000596±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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oocytes_trisopterus_nucleus_2f 912 25 2 0.00 0.00 0.00 nan± nan 0.000589±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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oocytes_trisopterus_states_5b 912 32 3 0.00 0.00 0.00 nan± nan 0.000599±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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parkinsons 195 22 2 0.00 0.00 0.00 nan± nan 0.000516±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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pima 768 8 2 0.00 0.00 0.00 nan± nan 0.000550±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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pittsburg-bridges-MATERIAL 106 7 3 0.00 0.00 0.00 nan± nan 0.000501±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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pittsburg-bridges-REL-L 103 7 3 0.00 0.00 0.00 nan± nan 0.000501±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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pittsburg-bridges-SPAN 92 7 3 0.00 0.00 0.00 nan± nan 0.000500±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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pittsburg-bridges-T-OR-D 102 7 2 0.00 0.00 0.00 nan± nan 0.000503±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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planning 182 12 2 0.00 0.00 0.00 nan± nan 0.000510±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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post-operative 90 8 3 0.00 0.00 0.00 nan± nan 0.000502±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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seeds 210 7 3 0.00 0.00 0.00 nan± nan 0.000508±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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statlog-australian-credit 690 14 2 0.00 0.00 0.00 nan± nan 0.000553±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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statlog-german-credit 1000 24 2 0.00 0.00 0.00 nan± nan 0.000592±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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statlog-heart 270 13 2 0.00 0.00 0.00 nan± nan 0.000517±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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statlog-image 2310 18 7 0.00 0.00 0.00 nan± nan 0.000708±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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statlog-vehicle 846 18 4 0.00 0.00 0.00 nan± nan 0.000579±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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synthetic-control 600 60 6 0.00 0.00 0.00 nan± nan 0.000597±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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tic-tac-toe 958 9 2 0.00 0.00 0.00 nan± nan 0.000563±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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vertebral-column-2clases 310 6 2 0.00 0.00 0.00 nan± nan 0.000515±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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wine 178 13 3 0.00 0.00 0.00 nan± nan 0.000509±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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zoo 101 16 7 0.00 0.00 0.00 nan± nan 0.000505±0.0000 {"max_features": "sqrt", "splitter": "fcbf"}
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** Accuracy compared to stree_default (liblinear-ovr) .: nan
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Time: 0h 0m 4s
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