Added Binarizer in Preprocessing and Hyperparameter optimization in pipeline

This commit is contained in:
Tuan-Dat Tran
2021-05-18 17:18:26 +00:00
parent 8b647de135
commit b127bc6b84
4 changed files with 943 additions and 356 deletions

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@@ -0,0 +1,25 @@
,mean_fit_time,std_fit_time,mean_score_time,std_score_time,param_metric,param_n_neighbors,param_weights,params,split0_test_score,split1_test_score,split2_test_score,mean_test_score,std_test_score,rank_test_score
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1 mean_fit_time std_fit_time mean_score_time std_score_time param_metric param_n_neighbors param_weights params split0_test_score split1_test_score split2_test_score mean_test_score std_test_score rank_test_score
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3 0 0.3251535892486572 0.127680187632828 1156.720083475113 103.6800414474859 euclidean 3 uniform {'metric': 'euclidean', 'n_neighbors': 3, 'weights': 'uniform'} 0.9673755825788826 0.968714844377779 0.9698917818493518 0.9686607362686711 0.0010279463208361468 2
4 3 0.581209659576416 0.10390654521562699 1097.628236611684 49.50409271683481 euclidean 5 distance {'metric': 'euclidean', 'n_neighbors': 5, 'weights': 'distance'} 0.9670541597471474 0.9677505758825735 0.9693024750883961 0.968035736906039 0.0009397581516544441 3
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6 2 0.5214482148488363 0.1338813546209848 1234.2422309716542 11.319769031350406 euclidean 5 uniform {'metric': 'euclidean', 'n_neighbors': 5, 'weights': 'uniform'} 0.9659291798360744 0.9661970321958536 0.9679095681988642 0.9666785934102641 0.0008772724469576776 5
7 4 0.38950196901957196 0.10594237544622603 1119.6926170190175 64.25975988670193 euclidean 7 uniform {'metric': 'euclidean', 'n_neighbors': 7, 'weights': 'uniform'} 0.9643756361493545 0.9659827503080303 0.9674809814636237 0.9659464559736696 0.0012680116558989624 6
8 7 0.44870662689208984 0.1539214539086042 1095.8349254131317 95.22915205238016 euclidean 11 distance {'metric': 'euclidean', 'n_neighbors': 11, 'weights': 'distance'} 0.9646434885091337 0.9632506562382814 0.9647487410264652 0.9642142952579601 0.0006827491697964685 7
9 6 0.6263217926025391 0.045471428070326544 1231.947474082311 10.357145120994318 euclidean 11 uniform {'metric': 'euclidean', 'n_neighbors': 11, 'weights': 'uniform'} 0.9637327904858842 0.961911394439385 0.9634094074788385 0.9630178641347026 0.000793452595644972 8
10 9 0.6597681840260824 0.08367258300110442 1603.911631822586 11.793869730582724 manhattan 3 distance {'metric': 'manhattan', 'n_neighbors': 3, 'weights': 'distance'} 0.961161407832003 0.9625006696308994 0.9638915675559842 0.9625178816729623 0.0011146494876286455 9
11 11 0.743593692779541 0.12585558461284738 1623.6791274547577 20.225285349079297 manhattan 5 distance {'metric': 'manhattan', 'n_neighbors': 5, 'weights': 'distance'} 0.9598757165050624 0.9628220924626346 0.9633558341369335 0.9620178810348768 0.001530331488777754 10
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13 13 0.7563843727111816 0.0361495198811297 1650.8071510791779 2.759115546096175 manhattan 7 distance {'metric': 'manhattan', 'n_neighbors': 7, 'weights': 'distance'} 0.9593935822574597 0.9614828306637382 0.9609986070931105 0.9606250066714361 0.0008929063713852963 12
14 10 0.5714000860850016 0.200821086554179 1670.9476985931396 21.43965257048912 manhattan 5 uniform {'metric': 'manhattan', 'n_neighbors': 5, 'weights': 'uniform'} 0.9581078909305191 0.9610006964161354 0.9616950605378763 0.9602678826281769 0.0015534281409951467 13
15 12 0.7014182408650717 0.07630416360771637 1602.6147842407227 13.998164063202559 manhattan 7 uniform {'metric': 'manhattan', 'n_neighbors': 7, 'weights': 'uniform'} 0.9576793271548723 0.9597150050891948 0.9595521268616737 0.9589821530352469 0.0009236336882771337 14
16 15 0.5463813940684 0.20986627389723325 1621.221689303716 10.57220404161948 manhattan 11 distance {'metric': 'manhattan', 'n_neighbors': 11, 'weights': 'distance'} 0.9573043338511812 0.957036481491402 0.9578913532626165 0.9574107228683998 0.00035701578260487497 15
17 14 0.659561554590861 0.16166694480866448 1647.0242857138317 15.482865038769452 manhattan 11 uniform {'metric': 'manhattan', 'n_neighbors': 11, 'weights': 'uniform'} 0.9554829378046821 0.9555900787485938 0.9565520197149898 0.9558750120894218 0.00048071078572838955 16
18 19 5.247008244196574 3.982239002878492 1610.0853408177693 4.880005667545898 chebyshev 5 distance {'metric': 'chebyshev', 'n_neighbors': 5, 'weights': 'distance'} 0.798253602614239 0.8040392135854717 0.8051001821493625 0.8024643327830244 0.003008776051168824 17
19 21 20.442909558614094 10.268306972202161 1091.167144536972 373.74252764500056 chebyshev 7 distance {'metric': 'chebyshev', 'n_neighbors': 7, 'weights': 'distance'} 0.7973429045909894 0.8016285423474581 0.7997964213007608 0.7995892894130695 0.0017557240593918855 18
20 17 3.0204404989878335 3.242756624385942 1615.3644462426503 47.3978612160567 chebyshev 3 distance {'metric': 'chebyshev', 'n_neighbors': 3, 'weights': 'distance'} 0.7828788771629078 0.80393207264156 0.8089038894246223 0.7985716130763634 0.011280549953147328 19
21 23 27.638134558995564 4.867014100523201 734.1344640254974 31.858155565000086 chebyshev 11 distance {'metric': 'chebyshev', 'n_neighbors': 11, 'weights': 'distance'} 0.7919858573954036 0.7913965822038892 0.7912782599378549 0.7915535665123826 0.00030946900255889454 20
22 18 1.1796804269154866 0.7346351248980267 1684.378450314204 9.234898911008068 chebyshev 5 uniform {'metric': 'chebyshev', 'n_neighbors': 5, 'weights': 'uniform'} 0.783575293298334 0.7888251995500081 0.7891353262616522 0.7871786063699981 0.0025510708161656103 21
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24 16 0.6336509386698405 0.19319871048710188 1672.988091468811 6.364915306048909 chebyshev 3 uniform {'metric': 'chebyshev', 'n_neighbors': 3, 'weights': 'uniform'} 0.7702898162532812 0.7848074141533187 0.7878495660559306 0.7809822654875102 0.007662028670422474 23
25 22 21.680665890375774 3.469126600885206 794.0563353697459 13.966075572059058 chebyshev 11 uniform {'metric': 'chebyshev', 'n_neighbors': 11, 'weights': 'uniform'} 0.78052177639685 0.7794503669577328 0.7796528447444552 0.7798749960330128 0.0004647529399678837 24