Run
7790227

Run 7790227

Task 14964 (Supervised Classification) artificial-characters 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
0.9896 ± 0.0022
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9241 ± 0.0102
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9153 ± 0.0113
Cross-validation details (10-fold Crossvalidation)
KB relative information score
8943.0166 ± 6.5508
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.04 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.179 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
10218
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9245 ± 0.0102
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9242 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.2849
Cross-validation details (10-fold Crossvalidation)
Recall
0.9242 ± 0.0101
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2236 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2992 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1241 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4148 ± 0.0141
Cross-validation details (10-fold Crossvalidation)