Run
7789457

Run 7789457

Task 9950 (Supervised Classification) micro-mass Uploaded 09-09-2017 by Jan van Rijn
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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)(3)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.ensemble.forest.RandomForestClassifier(24)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(24)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(24)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(24)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(24)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(24)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(24)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(24)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(24)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(24)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(24)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(24)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(24)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(24)_random_state1
sklearn.ensemble.forest.RandomForestClassifier(24)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(24)_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.

17 Evaluation measures

Area under ROC curve
0.9819 ± 0.0075
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8145
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8078 ± 0.039
Cross-validation details (10-fold Crossvalidation)
KB relative information score
437.966 ± 1.8028
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0419 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0941 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
571
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8219
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8196 ± 0.0365
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.208
Cross-validation details (10-fold Crossvalidation)
Recall
0.8196 ± 0.0365
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4455 ± 0.0393
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2169 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1285 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5923 ± 0.0448
Cross-validation details (10-fold Crossvalidation)