Run
9918548

Run 9918548

Task 3902 (Supervised Classification) pc4 Uploaded 24-12-2018 by Pieter Gijsbers
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Flow

sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,cate ncoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_s election.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.R andomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(45)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(45)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(45)_criterion"entropy"
sklearn.ensemble.forest.RandomForestClassifier(45)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(45)_max_features0.48118081328191786
sklearn.ensemble.forest.RandomForestClassifier(45)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(45)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(45)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_leaf2
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_split6
sklearn.ensemble.forest.RandomForestClassifier(45)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(45)_n_estimators300
sklearn.ensemble.forest.RandomForestClassifier(45)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(45)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(45)_random_state7243
sklearn.ensemble.forest.RandomForestClassifier(45)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(45)_warm_startfalse
preprocessing.ConditionalImputer2(1)_axis0
preprocessing.ConditionalImputer2(1)_categorical_features[]
preprocessing.ConditionalImputer2(1)_copytrue
preprocessing.ConditionalImputer2(1)_fill_empty0
preprocessing.ConditionalImputer2(1)_missing_values"NaN"
preprocessing.ConditionalImputer2(1)_strategy"mean"
preprocessing.ConditionalImputer2(1)_strategy_nominal"most_frequent"
preprocessing.ConditionalImputer2(1)_verbose0
sklearn.feature_selection.variance_threshold.VarianceThreshold(20)_threshold0.0
sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,catencoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
preprocessing.MultiLabelEncoder(1)_colsnull

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.9423 ± 0.0215
Per class
Cross-validation details (10-fold Crossvalidation)
0.9076 ± 0.0216
Per class
Cross-validation details (10-fold Crossvalidation)
0.5515 ± 0.1014
Cross-validation details (10-fold Crossvalidation)
484.457 ± 14.6017
Cross-validation details (10-fold Crossvalidation)
0.1146 ± 0.0152
Cross-validation details (10-fold Crossvalidation)
0.2148 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
1458
Per class
Cross-validation details (10-fold Crossvalidation)
0.9054 ± 0.0229
Per class
Cross-validation details (10-fold Crossvalidation)
0.9115 ± 0.021
Cross-validation details (10-fold Crossvalidation)
0.5368
Cross-validation details (10-fold Crossvalidation)
0.9115 ± 0.021
Per class
Cross-validation details (10-fold Crossvalidation)
0.5337 ± 0.0683
Cross-validation details (10-fold Crossvalidation)
0.3274 ± 0.003
Cross-validation details (10-fold Crossvalidation)
0.2465 ± 0.0237
Cross-validation details (10-fold Crossvalidation)
0.7529 ± 0.0697
Cross-validation details (10-fold Crossvalidation)