Run
8846615

Run 8846615

Task 34536 (Supervised Classification) Internet-Advertisements Uploaded 26-01-2018 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)(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"mean"
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)_C5224.330802641384
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.4421965399115322
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree5
sklearn.svm.classes.SVC(17)_gamma0.00016030663204792935
sklearn.svm.classes.SVC(17)_kernel"sigmoid"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state32159
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol0.0030338101591177854
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
0.9307 ± 0.0252
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9451 ± 0.0112
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7634 ± 0.0472
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2220.2935 ± 20.774
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0717 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2409 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
3279
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9453 ± 0.0115
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9472 ± 0.0114
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5848
Cross-validation details (10-fold Crossvalidation)
Recall
0.9472 ± 0.0114
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2978 ± 0.0536
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.347 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2027 ± 0.0239
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5841 ± 0.0702
Cross-validation details (10-fold Crossvalidation)