Run
6058705

Run 6058705

Task 14967 (Supervised Classification) cjs Uploaded 02-08-2017 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"most_frequent"
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)_C0.23602352173432273
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.0015510765659446889
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state18264
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0003112645674932788
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
0.8298 ± 0.013
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.1889
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0963 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
KB relative information score
415.9548 ± 2.9751
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2561 ± 0.0019
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
0.4161
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2979 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5207
Cross-validation details (10-fold Crossvalidation)
Recall
0.2979 ± 0.0165
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9387 ± 0.0069
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3694 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3559 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9635 ± 0.0068
Cross-validation details (10-fold Crossvalidation)