Run
2082436

Run 2082436

Task 145682 (Supervised Classification) spectrometer Uploaded 21-04-2017 by Kelt Coolen
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Flow

weka.RandomizableFilteredClassifier_AttributeSelectedClassifier_SMO_PolyKer nel(1)Weka implementation of RandomizableFilteredClassifier
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.AttributeSelectedClassifier_SMO_PolyKernel(2)_Eweka.attributeSelection.CfsSubsetEval -P 1 -E 1
weka.AttributeSelectedClassifier_SMO_PolyKernel(2)_Sweka.attributeSelection.BestFirst -D 1 -N 5
weka.AttributeSelectedClassifier_SMO_PolyKernel(2)_Wweka.classifiers.functions.SMO
weka.RandomizableFilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel(1)_S1
weka.RandomizableFilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel(1)_Fweka.filters.unsupervised.attribute.RandomProjection -N 10 -R 42 -D Sparse1
weka.RandomizableFilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel(1)_Wweka.classifiers.meta.AttributeSelectedClassifier

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
0.8048
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.1306
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1858
Cross-validation details (10-fold Crossvalidation)
KB relative information score
25.6953
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0401
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
0.0926
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2524
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.8467
Cross-validation details (10-fold Crossvalidation)
Recall
0.2524
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0124
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1406
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.141
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0028
Cross-validation details (10-fold Crossvalidation)