Run
5910546

Run 5910546

Task 14968 (Supervised Classification) cylinder-bands Uploaded 13-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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"entropy"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.8577563178030854
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split10
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_state16296
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, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 20, 34, 36]
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, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 20, 34, 36]
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

0.8963 ± 0.0539
Per class
Cross-validation details (10-fold Crossvalidation)
0.8075 ± 0.0667
Per class
Cross-validation details (10-fold Crossvalidation)
0.603 ± 0.1357
Cross-validation details (10-fold Crossvalidation)
214.2593 ± 4.379
Cross-validation details (10-fold Crossvalidation)
0.3125 ± 0.0364
Cross-validation details (10-fold Crossvalidation)
0.4879 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
540
Per class
Cross-validation details (10-fold Crossvalidation)
0.8144 ± 0.0634
Per class
Cross-validation details (10-fold Crossvalidation)
0.8111 ± 0.0646
Cross-validation details (10-fold Crossvalidation)
0.9826
Cross-validation details (10-fold Crossvalidation)
0.8111 ± 0.0646
Per class
Cross-validation details (10-fold Crossvalidation)
0.6403 ± 0.075
Cross-validation details (10-fold Crossvalidation)
0.4939 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.3696 ± 0.0349
Cross-validation details (10-fold Crossvalidation)
0.7484 ± 0.0711
Cross-validation details (10-fold Crossvalidation)