Run
7835229

Run 7835229

Task 125920 (Supervised Classification) dresses-sales Uploaded 10-09-2017 by Jan van Rijn
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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[0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11]
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)_C1.0
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)_gamma"auto"
sklearn.svm.classes.SVC(8)_kernel"sigmoid"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state1
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.001
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
0.6534 ± 0.0634
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6253 ± 0.065
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2359 ± 0.1235
Cross-validation details (10-fold Crossvalidation)
KB relative information score
36.9596 ± 1.7733
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4576 ± 0.0137
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4873
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6493 ± 0.0675
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.65 ± 0.0519
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9816
Cross-validation details (10-fold Crossvalidation)
Recall
0.65 ± 0.0519
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9391 ± 0.0282
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4936
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4756 ± 0.013
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9635 ± 0.0263
Cross-validation details (10-fold Crossvalidation)