{"text_format":"3","workbook":"xlsx","n_sheets":2,"sheets":["Instruction","01_mAML_results_nofilter_noover"],"not_rendered":{"defined_names":1},"read":"whole","date_system":"1900"}

{"sheet":"Instruction","index":0,"n_rows":2,"n_cols":1,"rows_kept":2}
["Additional file 2: Comparison of prediction accuracy of different algorithms using the mAML machine pipeline for classification."]
["Results"]

{"sheet":"01_mAML_results_nofilter_noover","index":1,"n_rows":64,"n_cols":7,"rows_kept":64}
["Algorithm name","Scaler used","Algorithms parameters (Hyperparameters)","Mean test accuracy","Standard deviation of test accuracy","Mean train accuracy","Standard deviation of train accuracy"]
["Random Forest","NonScaler()","{'clf': RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\nmax_depth=None, max_features='auto', max_leaf_nodes=None,\nmin_impurity_decrease=0.0, min_impurity_split=None,\nmin_samples_leaf=1, min_samples_split=2,\nmin_weight_fraction_leaf=0.0, n_estimators=500,\nn_jobs=None, oob_score=False, random_state=0, verbose=0,\nwarm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Decision Tree","NonScaler()","{'clf': DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\nmax_features=None, max_leaf_nodes=None,\nmin_impurity_decrease=0.0, min_impurity_split=None,\nmin_samples_leaf=1, min_samples_split=2,\nmin_weight_fraction_leaf=0.0, presort=False,\nrandom_state=0, splitter='best'), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Bagging","NonScaler()","{'clf': BaggingClassifier(base_estimator=None, bootstrap=True, bootstrap_features=False,\nmax_features=1.0, max_samples=1.0, n_estimators=10,\nn_jobs=None, oob_score=False, random_state=0, verbose=0,\nwarm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Gradient Boosting","NonScaler()","{'clf': GradientBoostingClassifier(criterion='friedman_mse', init=None,\nlearning_rate=0.1, loss='deviance', max_depth=3,\nmax_features=None, max_leaf_nodes=None,\nmin_impurity_decrease=0.0, min_impurity_split=None,\nmin_samples_leaf=1, min_samples_split=2,\nmin_weight_fraction_leaf=0.0, n_estimators=100,\nn_iter_no_change=None, presort='auto',\nrandom_state=None, subsample=1.0, tol=0.0001,\nvalidation_fraction=0.1, verbose=0,\nwarm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Extra Trees","NonScaler()","{'clf': ExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini',\nmax_depth=None, max_features='auto', max_leaf_nodes=None,\nmin_impurity_decrease=0.0, min_impurity_split=None,\nmin_samples_leaf=1, min_samples_split=2,\nmin_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=None,\noob_score=False, random_state=0, verbose=0,\nwarm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["LGBM","NonScaler()","{'clf': LGBMClassifier(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\nimportance_type='split', learning_rate=0.1, max_depth=-1,\nmin_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,\nn_estimators=100, n_jobs=-1, num_leaves=31, objective=None,\nrandom_state=0, reg_alpha=0.0, reg_lambda=0.0, silent=True,\nsubsample=1.0, subsample_for_bin=200000, subsample_freq=0), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","NonScaler()","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","MinMaxScaler(copy=True, feature_range=(0, 1))","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': MinMaxScaler(copy=True, feature_range=(0, 1))}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","MaxAbsScaler(copy=True)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': MaxAbsScaler(copy=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","StandardScaler(copy=True, with_mean=True, with_std=True)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': StandardScaler(copy=True, with_mean=True, with_std=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","Normalizer(copy=True, norm='l2')","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': Normalizer(copy=True, norm='l2')}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","NonScaler()","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","MinMaxScaler(copy=True, feature_range=(0, 1))","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': MinMaxScaler(copy=True, feature_range=(0, 1))}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","MaxAbsScaler(copy=True)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': MaxAbsScaler(copy=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","StandardScaler(copy=True, with_mean=True, with_std=True)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': StandardScaler(copy=True, with_mean=True, with_std=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","NonScaler()","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","MinMaxScaler(copy=True, feature_range=(0, 1))","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': MinMaxScaler(copy=True, feature_range=(0, 1))}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","MaxAbsScaler(copy=True)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': MaxAbsScaler(copy=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","StandardScaler(copy=True, with_mean=True, with_std=True)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': StandardScaler(copy=True, with_mean=True, with_std=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","Normalizer(copy=True, norm='l2')","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': Normalizer(copy=True, norm='l2')}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","NonScaler()","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': NonScaler()}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","MinMaxScaler(copy=True, feature_range=(0, 1))","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': MinMaxScaler(copy=True, feature_range=(0, 1))}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","MaxAbsScaler(copy=True)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': MaxAbsScaler(copy=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","StandardScaler(copy=True, with_mean=True, with_std=True)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': StandardScaler(copy=True, with_mean=True, with_std=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","Normalizer(copy=True, norm='l2')","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': Normalizer(copy=True, norm='l2')}",{"v":1,"d":"1.00"},{"v":0,"d":"0.00"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":0.98615221987315,"d":"0.99"},{"v":0.011308312152487,"d":"0.01"}]
["Naive Bayes","PowerTransformer(copy=True, method='yeo-johnson', standardize=False)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': PowerTransformer(copy=True, method='yeo-johnson', standardize=False)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)}",{"v":0.981818181818182,"d":"0.98"},{"v":0.036363636363636,"d":"0.04"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","Binarizer(copy=True, threshold=0)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': Binarizer(copy=True, threshold=0)}",{"v":0.963636363636364,"d":"0.96"},{"v":0.072727272727273,"d":"0.07"},{"v":0.9723044397463,"d":"0.97"},{"v":0.017180760806689,"d":"0.02"}]
["LGBM","Normalizer(copy=True, norm='l2')","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': Normalizer(copy=True, norm='l2')}",{"v":0.963636363636364,"d":"0.96"},{"v":0.072727272727273,"d":"0.07"},{"v":0.976744186046512,"d":"0.98"},{"v":0.020800632348835,"d":"0.02"}]
["Naive Bayes","NonScaler()","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': NonScaler()}",{"v":0.945454545454546,"d":"0.95"},{"v":0.109090909090909,"d":"0.11"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","Binarizer(copy=True, threshold=0)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': Binarizer(copy=True, threshold=0)}",{"v":0.945454545454546,"d":"0.95"},{"v":0.072727272727273,"d":"0.07"},{"v":0.990803382663848,"d":"0.99"},{"v":0.011264749940598,"d":"0.01"}]
["Logistic Regression","Binarizer(copy=True, threshold=0)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': Binarizer(copy=True, threshold=0)}",{"v":0.945454545454546,"d":"0.95"},{"v":0.072727272727273,"d":"0.07"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["SVM Linear kernel","Binarizer(copy=True, threshold=0)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': Binarizer(copy=True, threshold=0)}",{"v":0.945454545454546,"d":"0.95"},{"v":0.072727272727273,"d":"0.07"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Ada Boost","NonScaler()","{'clf': AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0,\nn_estimators=50, random_state=0), 'scl': NonScaler()}",{"v":0.927272727272727,"d":"0.93"},{"v":0.106017307179005,"d":"0.11"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","Normalizer(copy=True, norm='l2')","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': Normalizer(copy=True, norm='l2')}",{"v":0.927272727272727,"d":"0.93"},{"v":0.106017307179005,"d":"0.11"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': FunctionTransformer(accept_sparse=False, check_inverse=True,\nfunc=<ufunc 'log1p'>, inv_kw_args=None, inverse_func=None,\nkw_args=None, pass_y='deprecated', validate=False)}",{"v":0.927272727272727,"d":"0.93"},{"v":0.106017307179005,"d":"0.11"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Stochastic Gradient Descent","Binarizer(copy=True, threshold=0)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': Binarizer(copy=True, threshold=0)}",{"v":0.927272727272727,"d":"0.93"},{"v":0.089072354283025,"d":"0.09"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","MinMaxScaler(copy=True, feature_range=(0, 1))","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': MinMaxScaler(copy=True, feature_range=(0, 1))}",{"v":0.909090909090909,"d":"0.91"},{"v":0.140835758043906,"d":"0.14"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","MaxAbsScaler(copy=True)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': MaxAbsScaler(copy=True)}",{"v":0.909090909090909,"d":"0.91"},{"v":0.140835758043906,"d":"0.14"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': RobustScaler(copy=True, quantile_range=(25, 75), with_centering=False,\nwith_scaling=True)}",{"v":0.909090909090909,"d":"0.91"},{"v":0.140835758043906,"d":"0.14"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","StandardScaler(copy=True, with_mean=True, with_std=True)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': StandardScaler(copy=True, with_mean=True, with_std=True)}",{"v":0.890909090909091,"d":"0.89"},{"v":0.145454545454545,"d":"0.15"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Naive Bayes","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='uniform', random_state=None,\nsubsample=100000)}",{"v":0.890909090909091,"d":"0.89"},{"v":0.145454545454545,"d":"0.15"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["Logistic Regression","PowerTransformer(copy=True, method='yeo-johnson', standardize=False)","{'clf': LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\nintercept_scaling=1, l1_ratio=0.15, max_iter=100,\nmulti_class='auto', n_jobs=None, penalty='elasticnet',\nrandom_state=0, solver='saga', tol=0.0001, verbose=0,\nwarm_start=False), 'scl': PowerTransformer(copy=True, method='yeo-johnson', standardize=False)}",{"v":0.872727272727273,"d":"0.87"},{"v":0.158505416128752,"d":"0.16"},{"v":0.880338266384778,"d":"0.88"},{"v":0.119105378587872,"d":"0.12"}]
["XGBoost","NonScaler()","{'clf': XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\ncolsample_bynode=1, colsample_bytree=1, gamma=0,\nlearning_rate=0.1, max_delta_step=0, max_depth=3,\nmin_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\nnthread=None, objective='binary:logistic', random_state=0,\nreg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\nsilent=None, subsample=1, verbosity=1), 'scl': NonScaler()}",{"v":0.869090909090909,"d":"0.87"},{"v":0.049326036240911,"d":"0.05"},{"v":1,"d":"1.00"},{"v":0,"d":"0.00"}]
["K-Neighbors","PowerTransformer(copy=True, method='yeo-johnson', standardize=False)","{'clf': KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\nmetric_params=None, n_jobs=None, n_neighbors=5, p=2,\nweights='uniform'), 'scl': PowerTransformer(copy=True, method='yeo-johnson', standardize=False)}",{"v":0.832727272727273,"d":"0.83"},{"v":0.202920820775327,"d":"0.20"},{"v":0.953488372093023,"d":"0.95"},{"v":0.070538376223735,"d":"0.07"}]
["SVM Linear kernel","PowerTransformer(copy=True, method='yeo-johnson', standardize=False)","{'clf': LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,\nintercept_scaling=1, loss='squared_hinge', max_iter=1000,\nmulti_class='ovr', penalty='l2', random_state=0, tol=0.0001,\nverbose=0), 'scl': PowerTransformer(copy=True, method='yeo-johnson', standardize=False)}",{"v":0.827272727272727,"d":"0.83"},{"v":0.191557340960959,"d":"0.19"},{"v":0.958139534883721,"d":"0.96"},{"v":0.083720930232558,"d":"0.08"}]
["Stochastic Gradient Descent","PowerTransformer(copy=True, method='yeo-johnson', standardize=False)","{'clf': SGDClassifier(alpha=0.0001, average=False, class_weight=None,\nearly_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,\nl1_ratio=0.15, learning_rate='optimal', loss='hinge',\nmax_iter=1000, n_iter_no_change=5, n_jobs=None,\npenalty='elasticnet', power_t=0.5, random_state=0, shuffle=True,\ntol=0.001, validation_fraction=0.1, verbose=0, warm_start=False), 'scl': PowerTransformer(copy=True, method='yeo-johnson', standardize=False)}",{"v":0.778181818181818,"d":"0.78"},{"v":0.146991875864784,"d":"0.15"},{"v":0.925581395348837,"d":"0.93"},{"v":0.101262981660824,"d":"0.10"}]
["Naive Bayes","QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)","{'clf': GaussianNB(priors=None, var_smoothing=1e-09), 'scl': QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,\noutput_distribution='normal', random_state=None,\nsubsample=100000)}",{"v":0.727272727272727,"d":"0.73"},{"v":0.162623125636348,"d":"0.16"},{"v":0.874524312896406,"d":"0.87"},{"v":0.096111759594813,"d":"0.10"}]