Run
5926169

Run 5926169

Task 2079 (Supervised Classification) eucalyptus Uploaded 13-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
Issue #Downvotes for this reason By


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)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(21)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(21)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(21)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.4374564761408454
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf16
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split17
sklearn.ensemble.forest.RandomForestClassifier(21)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(21)_n_estimators100
sklearn.ensemble.forest.RandomForestClassifier(21)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(21)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(21)_random_state47559
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[0, 2, 3, 4, 9]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 2, 3, 4, 9]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0

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

0.9007 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
0.6459 ± 0.0493
Per class
Cross-validation details (10-fold Crossvalidation)
0.5492 ± 0.0605
Cross-validation details (10-fold Crossvalidation)
352.4435 ± 2.1641
Cross-validation details (10-fold Crossvalidation)
0.2046 ± 0.008
Cross-validation details (10-fold Crossvalidation)
0.3132 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
736
Per class
Cross-validation details (10-fold Crossvalidation)
0.6665 ± 0.0384
Per class
Cross-validation details (10-fold Crossvalidation)
0.6535 ± 0.046
Cross-validation details (10-fold Crossvalidation)
2.2629
Cross-validation details (10-fold Crossvalidation)
0.6535 ± 0.046
Per class
Cross-validation details (10-fold Crossvalidation)
0.6533 ± 0.0255
Cross-validation details (10-fold Crossvalidation)
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.3065 ± 0.0088
Cross-validation details (10-fold Crossvalidation)
0.7746 ± 0.0224
Cross-validation details (10-fold Crossvalidation)