Run 5952847

Task 9956 (Supervised Classification) one-hundred-plants-texture Uploaded 14-07-2017 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=skle arn.tree.tree.DecisionTreeClassifier))(1)	Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(10)_class_weight	null
sklearn.tree.tree.DecisionTreeClassifier(10)_criterion	"gini"
sklearn.tree.tree.DecisionTreeClassifier(10)_max_depth	2
sklearn.tree.tree.DecisionTreeClassifier(10)_max_features	null
sklearn.tree.tree.DecisionTreeClassifier(10)_max_leaf_nodes	null
sklearn.tree.tree.DecisionTreeClassifier(10)_min_impurity_split	1e-07
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_leaf	1
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_split	2
sklearn.tree.tree.DecisionTreeClassifier(10)_min_weight_fraction_leaf	0.0
sklearn.tree.tree.DecisionTreeClassifier(10)_presort	false
sklearn.tree.tree.DecisionTreeClassifier(10)_random_state	45803
sklearn.tree.tree.DecisionTreeClassifier(10)_splitter	"best"
openmlstudy14.preprocessing.ConditionalImputer(2)_axis	0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features	[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copy	true
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty	0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values	"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy	"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal	"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose	0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features	[]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown	"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values	"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparse	false
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold	0.0
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_algorithm	"SAMME"
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_learning_rate	0.19193376577130608
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_n_estimators	50
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_random_state	34417