Run
6005148

Run 6005148

Task 2074 (Supervised Classification) satimage Uploaded 17-07-2017 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)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C18.79556542426367
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.020844047046333358
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.0016967070972737765
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state22562
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.033314616334149755
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
0.9595 ± 0.0057
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7724 ± 0.0148
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7145 ± 0.0194
Cross-validation details (10-fold Crossvalidation)
KB relative information score
4429.0619 ± 9.51
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1099 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2701 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
6430
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7839 ± 0.0124
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7697 ± 0.0158
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.4836
Cross-validation details (10-fold Crossvalidation)
Recall
0.7697 ± 0.0158
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4067 ± 0.0154
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3675 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.225 ± 0.007
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6124 ± 0.0189
Cross-validation details (10-fold Crossvalidation)