Run
6056900

Run 6056900

Task 3950 (Supervised Classification) musk Uploaded 28-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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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.svm.classes.SVC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[0]
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[0]
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)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C0.2455751601964258
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.022695074473304544
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree1
sklearn.svm.classes.SVC(8)_gamma0.016693837767876737
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state57397
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.01934248398302097
sklearn.svm.classes.SVC(8)_verbosefalse

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
0.9724 ± 0.0086
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9575 ± 0.0064
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8328 ± 0.0267
Cross-validation details (10-fold Crossvalidation)
KB relative information score
4665.0149 ± 15.8877
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0744 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2608 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Number of instances
6598
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9577 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9586 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6204
Cross-validation details (10-fold Crossvalidation)
Recall
0.9586 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2854 ± 0.0197
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3611 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1832 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5072 ± 0.0279
Cross-validation details (10-fold Crossvalidation)