Run
6010017

Run 6010017

Task 21 (Supervised Classification) car Uploaded 17-07-2017 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, 2, 3, 4, 5]
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, 1, 2, 3, 4, 5]
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
sklearn.svm.classes.SVC(8)_C0.22815298709772566
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.4478676745202397
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.21357430176063966
sklearn.svm.classes.SVC(8)_kernel"sigmoid"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state63431
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol1.7486037909937384e-05
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
0.9832 ± 0.005
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9087 ± 0.018
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8022 ± 0.0384
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1323.5489 ± 5.4084
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0661 ± 0.008
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
1728
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9115 ± 0.0174
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9074 ± 0.0177
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2099
Cross-validation details (10-fold Crossvalidation)
Recall
0.9074 ± 0.0177
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2888 ± 0.0353
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1783 ± 0.0156
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5275 ± 0.0462
Cross-validation details (10-fold Crossvalidation)