Run
5828497

Run 5828497

Task 3543 (Supervised Classification) irish Uploaded 13-07-2017 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, 2, 4]
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, 2, 4]
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)_C151.95486497028594
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)_gamma0.12619062358258387
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_state49854
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0003128463786307616
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
0.896 ± 0.0567
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7934 ± 0.0747
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5807 ± 0.1501
Cross-validation details (10-fold Crossvalidation)
KB relative information score
242.4819 ± 4.5089
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2672 ± 0.0396
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4938 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7935 ± 0.0772
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.794 ± 0.0743
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.991
Cross-validation details (10-fold Crossvalidation)
Recall
0.794 ± 0.0743
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5412 ± 0.0797
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4969 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3625 ± 0.0493
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7295 ± 0.0986
Cross-validation details (10-fold Crossvalidation)