Run
5991467

Run 5991467

Task 9979 (Supervised Classification) cardiotocography Uploaded 17-07-2017 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"gini"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.5792485370355185
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf20
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split2
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_state50037
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
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

1
Per class
Cross-validation details (10-fold Crossvalidation)
1
Per class
Cross-validation details (10-fold Crossvalidation)
1
Cross-validation details (10-fold Crossvalidation)
2101.6316 ± 0.6474
Cross-validation details (10-fold Crossvalidation)
0.0038 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.1679 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
2126
Per class
Cross-validation details (10-fold Crossvalidation)
1
Per class
Cross-validation details (10-fold Crossvalidation)
1
Cross-validation details (10-fold Crossvalidation)
2.9174
Cross-validation details (10-fold Crossvalidation)
1
Per class
Cross-validation details (10-fold Crossvalidation)
0.0226 ± 0.005
Cross-validation details (10-fold Crossvalidation)
0.2897 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.0177 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
0.0611 ± 0.0153
Cross-validation details (10-fold Crossvalidation)