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titanic.csv
We can make this file beautiful and searchable if this error is corrected: It looks like row 2 should actually have 1 column, instead of 11 in line 1.
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titanic.csv
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feature_selection;transformer;scaler;classifier;acc;f1;auc;acc-std;f1-std;auc-std
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OneHotEncoder(handle_unknown='ignore')();MaxAbsScaler();RandomForestClassifier(max_depth=10);0.8182223338145753;0.7341228681472248;0.8667041085312904;0.030039373476370763;0.06317352224171452;0.033065411900047956
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OneHotEncoder(handle_unknown='ignore')();MaxAbsScaler();LogisticRegression(max_iter=500);0.806973824618668;0.737435838590349;0.8504162632158005;0.01322294602293661;0.03197414629613858;0.02558852024688653
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OneHotEncoder(handle_unknown='ignore')();MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.7991023790094782;0.6980368313199703;0.8388261560603363;0.022251714657069238;0.0529536003250044;0.03791264838971474
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OneHotEncoder(handle_unknown='ignore')();MaxAbsScaler();LGBMClassifier();0.8249576297784195;0.7649745912796357;0.8654217231995365;0.03507851210933316;0.05475959291612837;0.035895104103512536
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1)();MaxAbsScaler();RandomForestClassifier(max_depth=10);0.8170861841692298;0.7468271449062686;0.8713230383624744;0.021284497087019443;0.04408888948969096;0.03635854872696295
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1)();MaxAbsScaler();LogisticRegression(max_iter=500);0.7934906785512522;0.7210617475400315;0.8493023019699436;0.03471704427849374;0.04438322374653045;0.019617654025666554
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1)();MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.797966229364133;0.6969839508800675;0.8416966131455558;0.030095354019713864;0.04721197943658406;0.03769977018557729
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TransformStrategy_OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1)();MaxAbsScaler();LGBMClassifier();0.8148327160881299;0.755175905486518;0.8682382935241237;0.0273535014293659;0.04581172493722859;0.03440396153643218
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_SingleStrategy();MaxAbsScaler();RandomForestClassifier(max_depth=10);0.8181721172556651;0.7494704500711127;0.8449883851176155;0.0343695484892876;0.0436788433980148;0.04944648268573175
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_SingleStrategy();MaxAbsScaler();LogisticRegression(max_iter=500);0.77890276818781;0.7092206703313684;0.8345774724167333;0.0319004911600143;0.03856766103659178;0.027690993256144426
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_SingleStrategy();MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.7979850605737242;0.6941979407328586;0.8277986292944721;0.029941866699575773;0.05453834407924222;0.03365196926020674
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_SingleStrategy();MaxAbsScaler();LGBMClassifier();0.8114430983616847;0.7449453173642067;0.8405740364380657;0.03825265379201424;0.050839234519798535;0.04638050070667639
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_SingleStrategy();MaxAbsScaler();DNN;0.7688217939865671;0.6265869342256053;0.8444041330940678;0.02298225715987228;0.06328541409232623;0.020482517506393818
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max2Strategy();MaxAbsScaler();RandomForestClassifier(max_depth=10);0.8069926558282594;0.7350465404018595;0.8353382779621343;0.03379403259910242;0.05249762237129228;0.04740159122262927
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max2Strategy();MaxAbsScaler();LogisticRegression(max_iter=500);0.7766618542464377;0.7073980443281174;0.8328577207942214;0.03156736655849527;0.04044261608006922;0.02979105449016765
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max2Strategy();MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.7822735547046638;0.6836301854557433;0.8199115479428191;0.021448544274522818;0.037640278199232394;0.03685232060962539
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max2Strategy();MaxAbsScaler();LGBMClassifier();0.7935220639005711;0.7238263670408536;0.827578902777675;0.02814654680475624;0.04632195844311065;0.04823042215962403
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max2Strategy();MaxAbsScaler();DNN;0.7957441466323519;0.6740871341993696;0.8502727062132092;0.03306464053212303;0.05812210332478761;0.027635675230207508
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max50Strategy();MaxAbsScaler();RandomForestClassifier(max_depth=10);0.7991400414286611;0.7226793073464957;0.843664079547237;0.04632145513544165;0.0665084256727676;0.04764276226541458
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max50Strategy();MaxAbsScaler();LogisticRegression(max_iter=500);0.7778042809616471;0.7118251640832286;0.8190262806518763;0.025294192755544696;0.04460185917190143;0.04371932590367062
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max50Strategy();MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.7901010608248069;0.6871126027776274;0.8180532356729031;0.028162894330204385;0.03617667414115335;0.048008173759218724
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max50Strategy();MaxAbsScaler();LGBMClassifier();0.8114807607808675;0.7453965273159623;0.8625275893846129;0.03714720676746586;0.055893722765347986;0.032831991989596056
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');TFEmbeddingWrapper_Max50Strategy();MaxAbsScaler();DNN;0.7822986629841189;0.6623905528238418;0.8427009931425994;0.04014907926963447;0.06673486445035748;0.03151961816751254
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');MeanTargetEncoder(alpha=5);MaxAbsScaler();RandomForestClassifier(max_depth=10);0.8148138848785388;0.7361746188658624;0.8365882296508987;0.02837317686039426;0.04468319696359982;0.030276449811009916
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');MeanTargetEncoder(alpha=5);MaxAbsScaler();LogisticRegression(max_iter=500);0.7856568953612454;0.7122560261550139;0.8458439675647782;0.02265738126484319;0.04393714171815591;0.023494230458108074
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');MeanTargetEncoder(alpha=5);MaxAbsScaler();KNeighborsClassifier(n_neighbors=10);0.8069424392693492;0.7081359644436378;0.8414511501162718;0.025449448712797397;0.0382007766958174;0.0369859179765843
FeatureSelection(categoricals=['pclass', 'sex', 'sibsp', 'parch', 'cabin', 'embarked', 'missing_age', 'cabin_type'], numericals=['age', 'fare'], target='survived');MeanTargetEncoder(alpha=5);MaxAbsScaler();LGBMClassifier();0.7845207457158999;0.690860870124028;0.8109374518578842;0.0385686396583843;0.07729071686913315;0.040245728071504394