Run
9079042

Run 9079042

Task 146818 (Supervised Classification) Australian Uploaded 14-04-2018 by Hilde Weerts
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  • openml-python Sklearn_0.19.1. study_98
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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[0, 3, 4, 5, 7, 8, 10, 11]
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"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_features0.5251715707163639
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf19
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split12
sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators300
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state45583
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_startfalse
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)_memorynull
hyperimp.utils.preprocessing.ConditionalImputer2(1)_axis0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_categorical_features[0, 3, 4, 5, 7, 8, 10, 11]
hyperimp.utils.preprocessing.ConditionalImputer2(1)_copytrue
hyperimp.utils.preprocessing.ConditionalImputer2(1)_fill_empty0
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)_verbose0

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
0.9324 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8626 ± 0.0372
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7226 ± 0.0733
Cross-validation details (10-fold Crossvalidation)
KB relative information score
426.1399 ± 2.9811
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2021 ± 0.0198
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.494 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
690
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8637 ± 0.0331
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8623 ± 0.0369
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9913
Cross-validation details (10-fold Crossvalidation)
Recall
0.8623 ± 0.0369
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4091 ± 0.04
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.497 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3117 ± 0.0306
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6272 ± 0.0613
Cross-validation details (10-fold Crossvalidation)