Run
8784093

Run 8784093

Task 9952 (Supervised Classification) phoneme 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_features0.13132007791879358
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf15
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split10
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_state10994
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"most_frequent"
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
0.9363 ± 0.0135
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.87 ± 0.0186
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6838 ± 0.0459
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2668.7983 ± 14.8888
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2152 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
5404
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8694 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8712 ± 0.018
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8733
Cross-validation details (10-fold Crossvalidation)
Recall
0.8712 ± 0.018
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5189 ± 0.0243
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3081 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6765 ± 0.0288
Cross-validation details (10-fold Crossvalidation)