Run
6049635

Run 6049635

Task 14967 (Supervised Classification) cjs Uploaded 27-07-2017 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, 1]
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, 1]
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)_C56.0244684968594
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.3219580539632123
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree4
sklearn.svm.classes.SVC(8)_gamma0.03253195985232863
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_state46037
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.001443553985740856
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
0.9889 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9263 ± 0.067
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9119 ± 0.0671
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1535.1932 ± 11.1512
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1717 ± 0.0107
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2729 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
2796
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9356 ± 0.0486
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9285 ± 0.0538
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5207
Cross-validation details (10-fold Crossvalidation)
Recall
0.9285 ± 0.0538
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6292 ± 0.0391
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3694 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2471 ± 0.0133
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6689 ± 0.0361
Cross-validation details (10-fold Crossvalidation)