Run
8784064

Run 8784064

Task 3903 (Supervised Classification) pc3 Uploaded 10-01-2018 by Vishal Chouskey
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  • openml-pimp openml-python Sklearn_0.18.2.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.forest.RandomForestClassifier)(4)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(14)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(14)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(14)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(14)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(14)_sparsetrue
sklearn.ensemble.forest.RandomForestClassifier(29)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features0.7835270305355445
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf6
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split14
sklearn.ensemble.forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(29)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(29)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_random_state40804
sklearn.ensemble.forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(29)_warm_startfalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(9)_threshold0.0
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_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
0.8122 ± 0.0547
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.874 ± 0.0147
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2343 ± 0.0774
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-194.4423 ± 26.0363
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1467 ± 0.0156
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1842 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
1563
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8661 ± 0.0186
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8912 ± 0.0178
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.478
Cross-validation details (10-fold Crossvalidation)
Recall
0.8912 ± 0.0178
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7967 ± 0.0853
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3031 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2846 ± 0.0191
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.939 ± 0.0635
Cross-validation details (10-fold Crossvalidation)