Run
10228868

Run 10228868

Task 32 (Supervised Classification) pendigits 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_state39814
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
0.5012 ± 0.0088
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.1011 ± 0.0156
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0025 ± 0.0176
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0618 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1794 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
10992
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.1024 ± 0.0164
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.1032 ± 0.0158
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3208 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Recall
0.1032 ± 0.0158
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9967 ± 0.0176
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4235 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.4118 ± 0.0125
Cross-validation details (10-fold Crossvalidation)