Run
8829328

Run 8829328

Task 3889 (Supervised Classification) sylva_agnostic Uploaded 24-01-2018 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"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)_C13306.63761702852
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.41563633833590763
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree4
sklearn.svm.classes.SVC(17)_gamma4.751348530277126e-05
sklearn.svm.classes.SVC(17)_kernel"rbf"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state10581
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol0.00020325885337747933
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
0.9984 ± 0.0009
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9919 ± 0.0026
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.93 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
KB relative information score
12126.9673 ± 40.1243
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0142 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1156 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
14395
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9919 ± 0.0026
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9919 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3338
Cross-validation details (10-fold Crossvalidation)
Recall
0.9919 ± 0.0026
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1233 ± 0.0169
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2403 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0798 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3319 ± 0.0383
Cross-validation details (10-fold Crossvalidation)