Run
8810545

Run 8810545

Task 34536 (Supervised Classification) Internet-Advertisements Uploaded 23-01-2018 by Jan van Rijn
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-pimp openml-python Sklearn_0.18.1.
Issue #Downvotes for this reason By


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"median"
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)_C256.88962142305854
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.39285459124923494
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree2
sklearn.svm.classes.SVC(17)_gamma0.03458661014284765
sklearn.svm.classes.SVC(17)_kernel"poly"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state9566
sklearn.svm.classes.SVC(17)_shrinkingfalse
sklearn.svm.classes.SVC(17)_tol0.0006020868688176156
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
0.9421 ± 0.0272
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9577 ± 0.0158
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.819 ± 0.0732
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2152.7153 ± 22.4251
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0873 ± 0.013
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
0.9581 ± 0.0146
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9591 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5848
Cross-validation details (10-fold Crossvalidation)
Recall
0.9591 ± 0.0141
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3623 ± 0.0545
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
0.1907 ± 0.0282
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5496 ± 0.082
Cross-validation details (10-fold Crossvalidation)