OpenML
9918546

Run 9918546

Task 3549 (Supervised Classification) analcatdata_authorship 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

0.9989 ± 0.0011
Per class
Cross-validation details (10-fold Crossvalidation)
0.975 ± 0.0155
Per class
Cross-validation details (10-fold Crossvalidation)
0.9636 ± 0.0221
Cross-validation details (10-fold Crossvalidation)
772.4033 ± 1.0859
Cross-validation details (10-fold Crossvalidation)
0.0389 ± 0.0051
Cross-validation details (10-fold Crossvalidation)
0.3439 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
841
Per class
Cross-validation details (10-fold Crossvalidation)
0.9754 ± 0.0142
Per class
Cross-validation details (10-fold Crossvalidation)
0.975 ± 0.0153
Cross-validation details (10-fold Crossvalidation)
1.7898
Cross-validation details (10-fold Crossvalidation)
0.975 ± 0.0153
Per class
Cross-validation details (10-fold Crossvalidation)
0.113 ± 0.0147
Cross-validation details (10-fold Crossvalidation)
0.4146 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
0.107 ± 0.0156
Cross-validation details (10-fold Crossvalidation)
0.2581 ± 0.0373
Cross-validation details (10-fold Crossvalidation)