OpenML
8709830

Run 8709830

Task 3510 (Supervised Classification) JapaneseVowels Uploaded 28-12-2017 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. study_71
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)_C0.1180505249544205
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.5334244285215004
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree3
sklearn.svm.classes.SVC(17)_gamma0.1275022504659477
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_state61328
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol0.07347764853786648
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
0.8001 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.3659 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3257 ± 0.0163
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2332.3658 ± 6.5639
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1746 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1962 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
9961
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.3606 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4081 ± 0.0142
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.1321
Cross-validation details (10-fold Crossvalidation)
Recall
0.4081 ± 0.0142
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8898 ± 0.0053
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3132 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2915 ± 0.0017
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9309 ± 0.0054
Cross-validation details (10-fold Crossvalidation)