Run
8962637

Run 8962637

Task 3549 (Supervised Classification) analcatdata_authorship Uploaded 07-04-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(2)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.svm.classes.SVC(11)_C120.38702890658114
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef00.041231328829159475
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree3
sklearn.svm.classes.SVC(11)_gamma1.4492929632814055e-05
sklearn.svm.classes.SVC(11)_kernel"poly"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state11594
sklearn.svm.classes.SVC(11)_shrinkingtrue
sklearn.svm.classes.SVC(11)_tol0.000570196268566845
sklearn.svm.classes.SVC(11)_verbosefalse
sklearn.preprocessing.data.StandardScaler(7)_copytrue
sklearn.preprocessing.data.StandardScaler(7)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(7)_with_stdtrue

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
0.9878 ± 0.0252
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9413 ± 0.0338
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9155 ± 0.0467
Cross-validation details (10-fold Crossvalidation)
KB relative information score
707.5331 ± 12.3869
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0717 ± 0.0702
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3439 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Number of instances
841
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.942 ± 0.0241
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9417 ± 0.0325
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.7898
Cross-validation details (10-fold Crossvalidation)
Recall
0.9417 ± 0.0325
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2086 ± 0.2028
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4146 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1762 ± 0.075
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4249 ± 0.1793
Cross-validation details (10-fold Crossvalidation)