Run
9095497

Run 9095497

Task 146824 (Supervised Classification) mfeat-pixel Uploaded 14-04-2018 by Hilde Weerts
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  • openml-python Sklearn_0.19.1. study_98
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Flow

sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=skl earn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_se lection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1 )Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(17)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
sklearn.svm.classes.SVC(16)_C6.09384505760854
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.6668316904633248
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma0.26469825724761425
sklearn.svm.classes.SVC(16)_kernel"rbf"
sklearn.svm.classes.SVC(16)_max_iter-1
sklearn.svm.classes.SVC(16)_probabilityfalse
sklearn.svm.classes.SVC(16)_random_state96355
sklearn.svm.classes.SVC(16)_shrinkingtrue
sklearn.svm.classes.SVC(16)_tol0.0013083648301824478
sklearn.svm.classes.SVC(16)_verbosefalse
hyperimp.utils.preprocessing.ConditionalImputer2(1)_axis0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_categorical_features[]
hyperimp.utils.preprocessing.ConditionalImputer2(1)_copytrue
hyperimp.utils.preprocessing.ConditionalImputer2(1)_fill_empty0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_missing_values"NaN"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy"mean"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy_nominal"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_verbose0
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)_memorynull

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
0.5186 ± 0.0056
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.081
Per class
Kappa
0.0372 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
KB relative information score
187.7023 ± 2.0944
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1733 ± 0.002
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9103
Per class
Predictive accuracy
0.1335 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.1335 ± 0.01
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9628 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4163 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3876 ± 0.008
Cross-validation details (10-fold Crossvalidation)