Run
9921433

Run 9921433

Task 12 (Supervised Classification) mfeat-factors Uploaded 30-12-2018 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"gini"
sklearn.ensemble.forest.RandomForestClassifier(45)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(45)_max_features0.41663699808631327
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_leaf17
sklearn.ensemble.forest.RandomForestClassifier(45)_min_samples_split5
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_state65505
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

0.9971 ± 0.0015
Per class
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.015
Per class
Cross-validation details (10-fold Crossvalidation)
0.9233 ± 0.0167
Cross-validation details (10-fold Crossvalidation)
1746.1549 ± 2.0898
Cross-validation details (10-fold Crossvalidation)
0.0387 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
0.18
Cross-validation details (10-fold Crossvalidation)
2000
Per class
Cross-validation details (10-fold Crossvalidation)
0.9319 ± 0.0157
Per class
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.0151
Cross-validation details (10-fold Crossvalidation)
3.3219
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.0151
Per class
Cross-validation details (10-fold Crossvalidation)
0.2149 ± 0.0142
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)
0.1125 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
0.375 ± 0.0208
Cross-validation details (10-fold Crossvalidation)