Run
10398511

Run 10398511

Task 146825 (Supervised Classification) Fashion-MNIST Uploaded 10-09-2019 by Shao Wenbin
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Flow

sklearn.pipeline.Pipeline(scale=sklearn.preprocessing.data.StandardScaler,S VC=sklearn.svm.classes.LinearSVC)(1)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(scale=sklearn.preprocessing.data.StandardScaler,SVC=sklearn.svm.classes.LinearSVC)(1)_memorynull
sklearn.pipeline.Pipeline(scale=sklearn.preprocessing.data.StandardScaler,SVC=sklearn.svm.classes.LinearSVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "scale", "step_name": "scale"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "SVC", "step_name": "SVC"}}]
sklearn.pipeline.Pipeline(scale=sklearn.preprocessing.data.StandardScaler,SVC=sklearn.svm.classes.LinearSVC)(1)_verbosefalse
sklearn.preprocessing.data.StandardScaler(32)_copytrue
sklearn.preprocessing.data.StandardScaler(32)_with_meantrue
sklearn.preprocessing.data.StandardScaler(32)_with_stdtrue
sklearn.svm.classes.LinearSVC(11)_C0.01
sklearn.svm.classes.LinearSVC(11)_class_weightnull
sklearn.svm.classes.LinearSVC(11)_dualtrue
sklearn.svm.classes.LinearSVC(11)_fit_intercepttrue
sklearn.svm.classes.LinearSVC(11)_intercept_scaling1
sklearn.svm.classes.LinearSVC(11)_loss"squared_hinge"
sklearn.svm.classes.LinearSVC(11)_max_iter1000
sklearn.svm.classes.LinearSVC(11)_multi_class"ovr"
sklearn.svm.classes.LinearSVC(11)_penalty"l2"
sklearn.svm.classes.LinearSVC(11)_random_state1186
sklearn.svm.classes.LinearSVC(11)_tol0.0001
sklearn.svm.classes.LinearSVC(11)_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
0.9163 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8472 ± 0.0046
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8327 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.8425 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0301 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
70000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.847 ± 0.0046
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8494 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.8494 ± 0.0044
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1673 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1736 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5785 ± 0.0085
Cross-validation details (10-fold Crossvalidation)