Run
10439986

Run 10439986

Task 3560 (Supervised Classification) analcatdata_dmft Uploaded 06-04-2020 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,randomforestcla ssifier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(11)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(11)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(11)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(11)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(11)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(11)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(11)_sparsetrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_verbosefalse
sklearn.ensemble.forest.RandomForestClassifier(63)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(63)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(63)_criterion"entropy"
sklearn.ensemble.forest.RandomForestClassifier(63)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(63)_max_features0.3
sklearn.ensemble.forest.RandomForestClassifier(63)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(63)_min_impurity_decrease1e-07
sklearn.ensemble.forest.RandomForestClassifier(63)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(63)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(63)_min_samples_split3
sklearn.ensemble.forest.RandomForestClassifier(63)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(63)_n_estimators512
sklearn.ensemble.forest.RandomForestClassifier(63)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(63)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(63)_random_state1
sklearn.ensemble.forest.RandomForestClassifier(63)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(63)_warm_startfalse

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.

18 Evaluation measures

Area under ROC curve
0.5288 ± 0.0396
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.211 ± 0.0542
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0506 ± 0.0664
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.1256 ± 0.0315
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2715 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2774 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.2108 ± 0.0555
Cross-validation details (10-fold Crossvalidation)
Number of instances
797
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2119 ± 0.0545
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2108 ± 0.0555
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5803 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9786 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3724 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4041 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0851 ± 0.0271
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.2121 ± 0.0544
Cross-validation details (10-fold Crossvalidation)