Run
5984785

Run 5984785

Task 3917 (Supervised Classification) kc1 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[]
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[]
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)_C0.08396723060346445
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.620669090131502
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.015160770852169462
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_state27615
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol6.009229166909596e-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
0.7759 ± 0.0379
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.787 ± 0.0089
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0635 ± 0.0861
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-732.8145 ± 15.8494
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.27 ± 0.0117
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2616 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Number of instances
2109
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7794 ± 0.0156
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8402 ± 0.0131
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.622
Cross-validation details (10-fold Crossvalidation)
Recall
0.8402 ± 0.0131
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0323 ± 0.0422
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3615 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3479 ± 0.0098
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9623 ± 0.0294
Cross-validation details (10-fold Crossvalidation)