OpenML
10376777

Run 10376777

Task 16 (Supervised Classification) mfeat-karhunen Uploaded 25-08-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,svc=sklearn.svm.classes.SVC)(4)Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(30)_copytrue
sklearn.preprocessing.data.StandardScaler(30)_with_meantrue
sklearn.preprocessing.data.StandardScaler(30)_with_stdtrue
sklearn.svm.classes.SVC(32)_C1.0
sklearn.svm.classes.SVC(32)_cache_size200
sklearn.svm.classes.SVC(32)_class_weightnull
sklearn.svm.classes.SVC(32)_coef00.0
sklearn.svm.classes.SVC(32)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(32)_degree3
sklearn.svm.classes.SVC(32)_gamma"scale"
sklearn.svm.classes.SVC(32)_kernel"rbf"
sklearn.svm.classes.SVC(32)_max_iter-1
sklearn.svm.classes.SVC(32)_probabilityfalse
sklearn.svm.classes.SVC(32)_random_state1
sklearn.svm.classes.SVC(32)_shrinkingtrue
sklearn.svm.classes.SVC(32)_tol0.001
sklearn.svm.classes.SVC(32)_verbosefalse
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(4)_memorynull
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(4)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(4)_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
0.9867 ± 0.0043
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.976 ± 0.0077
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9733 ± 0.0086
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9749 ± 0.0081
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0048 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9762 ± 0.0076
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.976 ± 0.0077
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.976 ± 0.0077
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0267 ± 0.0086
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0693 ± 0.0109
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2309 ± 0.0363
Cross-validation details (10-fold Crossvalidation)