Run
9153604

Run 9153604

Task 167141 (Supervised Classification) churn Uploaded 15-04-2018 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[2, 4, 5, 19]
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_features0.5807911677846953
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_leaf1
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split3
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_state17963
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[2, 4, 5, 19]
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
0.9129 ± 0.0217
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9529 ± 0.007
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7986 ± 0.031
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3067.8122 ± 19.5816
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0894 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2429 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Number of instances
5000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9537 ± 0.0069
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9548 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5883
Cross-validation details (10-fold Crossvalidation)
Recall
0.9548 ± 0.0065
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3679 ± 0.0235
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3484 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1997 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.573 ± 0.0371
Cross-validation details (10-fold Crossvalidation)