Run
5977187

Run 5977187

Task 15 (Supervised Classification) breast-w Uploaded 16-07-2017 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[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
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)_C0.04541917889155369
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.5664327170294454
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree4
sklearn.svm.classes.SVC(8)_gamma0.6415416691314084
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_state61159
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0019384930516285212
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
0.9048 ± 0.069
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8909 ± 0.0329
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7531 ± 0.0748
Cross-validation details (10-fold Crossvalidation)
KB relative information score
439.3247 ± 4.6233
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1851 ± 0.0284
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4519 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Number of instances
699
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9057 ± 0.026
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8956 ± 0.0296
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9297
Cross-validation details (10-fold Crossvalidation)
Recall
0.8956 ± 0.0296
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4095 ± 0.0628
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4753 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2878 ± 0.0406
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6056 ± 0.0855
Cross-validation details (10-fold Crossvalidation)