Run
8978863

Run 8978863

Task 14968 (Supervised Classification) cylinder-bands Uploaded 08-04-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(2)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 20, 34, 36]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_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(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.svm.classes.SVC(11)_C0.8411172560117148
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef00.2974491153162182
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree2
sklearn.svm.classes.SVC(11)_gamma0.22695193527621502
sklearn.svm.classes.SVC(11)_kernel"poly"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state30901
sklearn.svm.classes.SVC(11)_shrinkingfalse
sklearn.svm.classes.SVC(11)_tol0.013147980482059729
sklearn.svm.classes.SVC(11)_verbosefalse
sklearn.preprocessing.data.StandardScaler(7)_copytrue
sklearn.preprocessing.data.StandardScaler(7)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(7)_with_stdtrue

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
0.8402 ± 0.0765
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7876 ± 0.0673
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5621 ± 0.137
Cross-validation details (10-fold Crossvalidation)
KB relative information score
187.8155 ± 4.7292
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3341 ± 0.041
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4879 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Number of instances
540
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7915 ± 0.0605
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7907 ± 0.0624
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9826
Cross-validation details (10-fold Crossvalidation)
Recall
0.7907 ± 0.0624
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6848 ± 0.0843
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4939 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3977 ± 0.039
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8052 ± 0.0791
Cross-validation details (10-fold Crossvalidation)