Yuta dataset
 

 

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Yuta (from FQS) after feature selection, CV = 10

Method Accuracy %  Reference Scheme  
DecisionStump 69.06 WEKA (T.W.) DecisionStump
SMO 68.68 WEKA (T.W.) SMO -C 1.0 -E 1.0 -A 1000003
-T 0.0010 -P 1.0E-12
DecisionTable 67.17 WEKA (T.W.) weka.classifiers.DecisionTable -X 1 -S 5
NaiveBayes 65.66 WEKA (T.W.) weka.classifiers.NaiveBayes -K
Logistic 64.53 WEKA (T.W.) Logistic
IBk 63.40 WEKA (T.W.) weka.classifiers.IBk -K 10 -W 0 -X
(k=7 wins) 
NaiveBayes 62.64 WEKA (T.W.) NaiveBayes
IB1 62.26 WEKA (T.W.) IB1
j48.PART 61.13 WEKA (T.W.) weka.classifiers.j48.PART -C 0.25 -M 2
kernelDensity 60.75 WEKA (T.W.) KernelDensity
j48.J48 60.75 WEKA (T.W.) weka.classifiers.j48.J48 -C 0.25 -M 2
kstar 60.38 WEKA (T.W.) weka.classifiers.kstar.KStar -B 20 -M a
ZeroR 60.38 WEKA (T.W.) ZeroR  DEFAULT
NaiveBayesSimple 57.74 WEKA (T.W.) NaiveBayesSimple  
adtree 57.36 WEKA (T.W.) weka.classifiers.adtree.ADTree -B 10 -E -3
OneR 56.98 WEKA (T.W.) OneR -B 6
VFI 49.43 WEKA (T.W.) weka.classifiers.VFI -B 0.6
HyperPipes 46.04 WEKA (T.W.) HyperPipes

 

Copyright(c) 2003 Tomasz Winiarski. All rights reserved.
twin at phys.uni.torun.pl