Run
8661849

Run 8661849

Task 14 (Supervised Classification) mfeat-fourier Uploaded 21-12-2017 by Vishal Chouskey
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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)_bootstraptrue
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_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split2
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_state1
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

0.9673 ± 0.0065
Per class
Cross-validation details (10-fold Crossvalidation)
0.7877 ± 0.0206
Per class
Cross-validation details (10-fold Crossvalidation)
0.7656 ± 0.0223
Cross-validation details (10-fold Crossvalidation)
1475.5886 ± 2.4313
Cross-validation details (10-fold Crossvalidation)
0.0742 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.18
Cross-validation details (10-fold Crossvalidation)
2000
Per class
Cross-validation details (10-fold Crossvalidation)
0.7917 ± 0.0217
Per class
Cross-validation details (10-fold Crossvalidation)
0.789 ± 0.0201
Cross-validation details (10-fold Crossvalidation)
3.3219
Cross-validation details (10-fold Crossvalidation)
0.789 ± 0.0201
Per class
Cross-validation details (10-fold Crossvalidation)
0.4121 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)
0.1777 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
0.5924 ± 0.0155
Cross-validation details (10-fold Crossvalidation)