OpenML
6180831

Run 6180831

Task 3494 (Supervised Classification) monks-problems-3 Uploaded 27-08-2017 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, 2, 3, 4, 5]
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, 2, 3, 4, 5]
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)_C825.7130366196025
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)_gamma0.18531432192479144
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_state56082
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.012881468369393299
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
0.9767 ± 0.0265
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9801 ± 0.029
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9602 ± 0.058
Cross-validation details (10-fold Crossvalidation)
KB relative information score
506.366 ± 2.8624
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0509 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4992 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
554
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9801 ± 0.0286
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9801 ± 0.029
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9989
Cross-validation details (10-fold Crossvalidation)
Recall
0.9801 ± 0.029
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.102 ± 0.0458
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4996 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1428 ± 0.0894
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2858 ± 0.1791
Cross-validation details (10-fold Crossvalidation)