sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar
dScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifie
r(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ens
emble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBoo
ster))(1) | Automatically created scikit-learn flow. |
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrap | True |
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weight | None |
sklearn.ensemble.forest.RandomForestClassifier(16)_criterion | entropy |
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depth | None |
sklearn.ensemble.forest.RandomForestClassifier(16)_max_features | 0.1 |
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodes | None |
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split | 1e-07 |
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf | 2 |
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split | 2 |
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf | 0.0 |
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators | 24 |
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs | -1 |
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_score | False |
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state | None |
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose | 0 |
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_start | False |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_criterion | friedman_mse |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_init | None |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_learning_rate | 0.01 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_loss | deviance |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth | 8 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_features | sqrt |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_leaf_nodes | None |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_impurity_split | 1e-07 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_leaf | 2 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_split | 2 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_weight_fraction_leaf | 0.0 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_n_estimators | 24 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presort | auto |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state | None |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample | 1.0 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose | 0 |
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_start | False |
sklearn.preprocessing.data.StandardScaler(1)_copy | True |
sklearn.preprocessing.data.StandardScaler(1)_with_mean | True |
sklearn.preprocessing.data.StandardScaler(1)_with_std | True |
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBooster))(1)_steps | [('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('votingclassifier', VotingClassifier(estimators=[('voting', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy',
max_depth=None, max_features=0.1, max_leaf_nodes=None,
min_impurity_split=1e-07, min_samples_leaf=2,
min_samples_split=2, min_weight_fraction_leaf=0.0,
...ogistic', reg_alpha=0, reg_lambda=1,
scale_pos_weight=1, seed=0, silent=True, subsample=0.8))],
n_jobs=-1, voting='soft', weights=[2, 3, 3]))] |
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBooster)(1)_estimators | [('voting', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy',
max_depth=None, max_features=0.1, max_leaf_nodes=None,
min_impurity_split=1e-07, min_samples_leaf=2,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=24, n_jobs=-1, oob_score=False, random_state=None,
verbose=0, warm_start=False)), ('weights', GradientBoostingClassifier(criterion='friedman_mse', init=None,
learning_rate=0.01, loss='deviance', max_depth=8,
max_features='sqrt', max_leaf_nodes=None,
min_impurity_split=1e-07, min_samples_leaf=2,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=24, presort='auto', random_state=None,
subsample=1.0, verbose=0, warm_start=False)), ('n_jobs', AUCBooster(base_score=0.5, colsample_bylevel=1, colsample_bytree=0.9, gamma=0,
learning_rate=0.01, max_delta_step=0, max_depth=8,
min_child_weight=2, missin |
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBooster)(1)_n_jobs | AUCBooster(base_score=0.5, colsample_bylevel=1, colsample_bytree=0.9, gamma=0,
learning_rate=0.01, max_delta_step=0, max_depth=8,
min_child_weight=2, missing=None, n_estimators=24, nthread=1,
objective='binary:logistic', reg_alpha=0, reg_lambda=1,
scale_pos_weight=1, seed=0, silent=True, subsample=0.8) |
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBooster)(1)_voting | RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy',
max_depth=None, max_features=0.1, max_leaf_nodes=None,
min_impurity_split=1e-07, min_samples_leaf=2,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=24, n_jobs=-1, oob_score=False, random_state=None,
verbose=0, warm_start=False) |
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=aucbooster.AUCBooster)(1)_weights | GradientBoostingClassifier(criterion='friedman_mse', init=None,
learning_rate=0.01, loss='deviance', max_depth=8,
max_features='sqrt', max_leaf_nodes=None,
min_impurity_split=1e-07, min_samples_leaf=2,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=24, presort='auto', random_state=None,
subsample=1.0, verbose=0, warm_start=False) |
aucbooster.AUCBooster(1)_base_score | 0.5 |
aucbooster.AUCBooster(1)_colsample_bylevel | 1 |
aucbooster.AUCBooster(1)_colsample_bytree | 0.9 |
aucbooster.AUCBooster(1)_gamma | 0 |
aucbooster.AUCBooster(1)_learning_rate | 0.01 |
aucbooster.AUCBooster(1)_max_delta_step | 0 |
aucbooster.AUCBooster(1)_max_depth | 8 |
aucbooster.AUCBooster(1)_min_child_weight | 2 |
aucbooster.AUCBooster(1)_missing | None |
aucbooster.AUCBooster(1)_n_estimators | 24 |
aucbooster.AUCBooster(1)_nthread | 1 |
aucbooster.AUCBooster(1)_objective | binary:logistic |
aucbooster.AUCBooster(1)_reg_alpha | 0 |
aucbooster.AUCBooster(1)_reg_lambda | 1 |
aucbooster.AUCBooster(1)_scale_pos_weight | 1 |
aucbooster.AUCBooster(1)_seed | 0 |
aucbooster.AUCBooster(1)_silent | True |
aucbooster.AUCBooster(1)_subsample | 0.8 |