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Run 9083668
Task 167119 (Supervised Classification)
jungle_chess_2pcs_raw_endgame_complete
Uploaded 14-04-2018 by
Hilde Weerts
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Evaluation Engine Exception: Run description file not present.
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By
Flow
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethr eshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=s klearn.ensemble.forest.RandomForestClassifier)(1)
Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features
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sklearn.preprocessing.data.OneHotEncoder(17)_dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown
"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values
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sklearn.preprocessing.data.OneHotEncoder(17)_sparse
true
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold
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sklearn.ensemble.forest.RandomForestClassifier(32)_bootstrap
true
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weight
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sklearn.ensemble.forest.RandomForestClassifier(32)_criterion
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sklearn.ensemble.forest.RandomForestClassifier(32)_max_features
0.9352643540573287
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodes
null
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease
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sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_split
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sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf
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sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split
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sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf
0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators
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sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs
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sklearn.ensemble.forest.RandomForestClassifier(32)_oob_score
false
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state
96587
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose
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sklearn.ensemble.forest.RandomForestClassifier(32)_warm_start
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sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memory
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hyperimp.utils.preprocessing.ConditionalImputer2(1)_categorical_features
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hyperimp.utils.preprocessing.ConditionalImputer2(1)_copy
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hyperimp.utils.preprocessing.ConditionalImputer2(1)_fill_empty
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hyperimp.utils.preprocessing.ConditionalImputer2(1)_missing_values
"NaN"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy
"mean"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy_nominal
"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_verbose
0
Result files
0 Evaluation measures