Run
2041926

Run 2041926

Task 145682 (Supervised Classification) spectrometer Uploaded 15-04-2017 by Stilyan Tonchev
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Flow

weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_MultiSearch_S MO_PolyKernel(1)Weka implementation of FilteredClassifier
weka.SMO_PolyKernel(15)_C1.0
weka.SMO_PolyKernel(15)_N0
weka.SMO_PolyKernel(15)_L0.001
weka.SMO_PolyKernel(15)_P1.0E-12
weka.SMO_PolyKernel(15)_V-1
weka.SMO_PolyKernel(15)_W1
weka.SMO_PolyKernel(15)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(15)_calibratortrue
weka.PolyKernel(11)_E1.0
weka.PolyKernel(11)_C250007
weka.MultiSearch_SMO_PolyKernel(1)_ECC
weka.MultiSearch_SMO_PolyKernel(1)_class-label1
weka.MultiSearch_SMO_PolyKernel(1)_search[weka.core.setupgenerator.MathParameter -property ridge -min -10.0 -max 5.0 -step 1.0 -base 10.0 -expression pow(BASE,I)]
weka.MultiSearch_SMO_PolyKernel(1)_algorithmweka.classifiers.meta.multisearch.DefaultSearch -sample-size 100.0 -initial-folds 2 -subsequent-folds 10 -initial-test-set . -subsequent-test-set . -num-slots 1 -num-slots 1
weka.MultiSearch_SMO_PolyKernel(1)_log-fileC:\Program Files\Weka-3-8
weka.MultiSearch_SMO_PolyKernel(1)_S1
weka.MultiSearch_SMO_PolyKernel(1)_Wweka.classifiers.functions.SMO
weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Fweka.filters.unsupervised.attribute.InterquartileRange -R first-last -O 3.0 -E 6.0
weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Wweka.classifiers.meta.FilteredClassifier
weka.FilteredClassifier_FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Fweka.filters.unsupervised.attribute.Standardize
weka.FilteredClassifier_FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Wweka.classifiers.meta.FilteredClassifier
weka.FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Fweka.filters.unsupervised.attribute.Remove -R 1
weka.FilteredClassifier_MultiSearch_SMO_PolyKernel(1)_Wweka.classifiers.meta.MultiSearch

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.9096
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4391
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4444
Cross-validation details (10-fold Crossvalidation)
KB relative information score
36.5739
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.04
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0396
Cross-validation details (10-fold Crossvalidation)
Number of instances
531
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.4446
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4765
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.8467
Cross-validation details (10-fold Crossvalidation)
Recall
0.4765
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0099
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1406
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1407
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0003
Cross-validation details (10-fold Crossvalidation)