Run
8778408

Run 8778408

Task 14964 (Supervised Classification) artificial-characters Uploaded 05-01-2018 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"entropy"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features0.3835035030871924
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf9
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split8
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_state46477
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"mean"
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
0.9754 ± 0.0017
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7363 ± 0.0105
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7054 ± 0.0115
Cross-validation details (10-fold Crossvalidation)
KB relative information score
7347.4459 ± 8.6675
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0816 ± 0.002
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
0.7382 ± 0.0108
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7361 ± 0.0103
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.2849
Cross-validation details (10-fold Crossvalidation)
Recall
0.7361 ± 0.0103
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4558 ± 0.0113
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2992 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1891 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.632 ± 0.0088
Cross-validation details (10-fold Crossvalidation)