Run
6050270

Run 6050270

Task 3567 (Supervised Classification) collins Uploaded 27-07-2017 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[19, 20]
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[19, 20]
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)_C0.03455914465353367
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.9194976705765983
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree5
sklearn.svm.classes.SVC(8)_gamma0.003969143075580351
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_state46304
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.006952280313281271
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
0.9983 ± 0.0021
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9566 ± 0.0378
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9537 ± 0.0352
Cross-validation details (10-fold Crossvalidation)
KB relative information score
398.9614 ± 1.6209
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0442 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1212 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9609 ± 0.0253
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.958 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.6642
Cross-validation details (10-fold Crossvalidation)
Recall
0.958 ± 0.0319
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3651 ± 0.032
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.246 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1102 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4479 ± 0.0408
Cross-validation details (10-fold Crossvalidation)