OpenML
9918561

Run 9918561

Task 9976 (Supervised Classification) madelon 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

Area under ROC curve
0.9297 ± 0.0137
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8627 ± 0.0162
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7254 ± 0.0324
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1398.5922 ± 9.3042
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2507 ± 0.0177
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.5
Cross-validation details (10-fold Crossvalidation)
Number of instances
2600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8627 ± 0.0161
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8627 ± 0.0162
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1
Cross-validation details (10-fold Crossvalidation)
Recall
0.8627 ± 0.0162
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5014 ± 0.0355
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.5
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3282 ± 0.0158
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6563 ± 0.0316
Cross-validation details (10-fold Crossvalidation)