Run
6142776

Run 6142776

Task 9954 (Supervised Classification) one-hundred-plants-margin Uploaded 26-08-2017 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[]
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)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C23314.1815256207
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)_gamma0.03718055062003694
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_state59207
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.00013021129303735518
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
0.9964 ± 0.0006
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8246
Per class
Kappa
0.8207 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
KB relative information score
982.8145 ± 1.3183
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0162 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0198
Cross-validation details (10-fold Crossvalidation)
Number of instances
1600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8326
Per class
Predictive accuracy
0.8225 ± 0.0229
Cross-validation details (10-fold Crossvalidation)
Prior entropy
6.6439
Cross-validation details (10-fold Crossvalidation)
Recall
0.8225 ± 0.0229
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8164 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.0995
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0829 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8335 ± 0.0075
Cross-validation details (10-fold Crossvalidation)