OpenML
8710121

Run 8710121

Task 14966 (Supervised Classification) Bioresponse Uploaded 28-12-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.preprocessing.data.StandardScaler(6)_copytrue
sklearn.preprocessing.data.StandardScaler(6)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(6)_with_stdtrue
sklearn.svm.classes.SVC(17)_C0.03768978786544316
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.9519832535130346
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree5
sklearn.svm.classes.SVC(17)_gamma0.0467151069096616
sklearn.svm.classes.SVC(17)_kernel"rbf"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state12607
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol3.324293610354429e-05
sklearn.svm.classes.SVC(17)_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
0.7145 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5531 ± 0.0165
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1854 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
KB relative information score
372.9886 ± 4.0269
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4512 ± 0.005
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6941 ± 0.0366
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6188 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.6188 ± 0.0136
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.909 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4727 ± 0.0048
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9489 ± 0.0095
Cross-validation details (10-fold Crossvalidation)