OpenML
10228888

Run 10228888

Task 9952 (Supervised Classification) phoneme Uploaded 26-06-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(feature_map=sklearn_extra.kernel_approximation._f astfood.Fastfood,svm=sklearn.svm.classes.LinearSVC)(1)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(feature_map=sklearn_extra.kernel_approximation._fastfood.Fastfood,svm=sklearn.svm.classes.LinearSVC)(1)_memorynull
sklearn.pipeline.Pipeline(feature_map=sklearn_extra.kernel_approximation._fastfood.Fastfood,svm=sklearn.svm.classes.LinearSVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "feature_map", "step_name": "feature_map"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svm", "step_name": "svm"}}]
sklearn.pipeline.Pipeline(feature_map=sklearn_extra.kernel_approximation._fastfood.Fastfood,svm=sklearn.svm.classes.LinearSVC)(1)_verbosefalse
sklearn_extra.kernel_approximation._fastfood.Fastfood(1)_n_components20
sklearn_extra.kernel_approximation._fastfood.Fastfood(1)_random_state1
sklearn_extra.kernel_approximation._fastfood.Fastfood(1)_sigma1.5811388300841898
sklearn_extra.kernel_approximation._fastfood.Fastfood(1)_tradeoff_mem_accuracy"mem"
sklearn.svm.classes.LinearSVC(10)_C1.0
sklearn.svm.classes.LinearSVC(10)_class_weightnull
sklearn.svm.classes.LinearSVC(10)_dualtrue
sklearn.svm.classes.LinearSVC(10)_fit_intercepttrue
sklearn.svm.classes.LinearSVC(10)_intercept_scaling1
sklearn.svm.classes.LinearSVC(10)_loss"squared_hinge"
sklearn.svm.classes.LinearSVC(10)_max_iter1000
sklearn.svm.classes.LinearSVC(10)_multi_class"ovr"
sklearn.svm.classes.LinearSVC(10)_penalty"l2"
sklearn.svm.classes.LinearSVC(10)_random_state40749
sklearn.svm.classes.LinearSVC(10)_tol0.0001
sklearn.svm.classes.LinearSVC(10)_verbose0

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
0.7162 ± 0.0172
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7788 ± 0.0133
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4548 ± 0.0333
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.4411 ± 0.0332
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.215 ± 0.0128
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
5404
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7769 ± 0.0141
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.785 ± 0.0128
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8732 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Recall
0.785 ± 0.0128
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5185 ± 0.0308
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4637 ± 0.0139
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0183 ± 0.0303
Cross-validation details (10-fold Crossvalidation)