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Table 2 Accuracy achieved on test set by different classifiers using various subsets of our 7 genes

From: A voting approach to identify a small number of highly predictive genes using multiple classifiers

Classifier Accuracy Gene Combination
C4.5 84.52% TSPYL5
C4.5 with boosting (ADABoost.M1) 91.67% TSPYL5-DIAPH1-AGTPBP1
C4.5 with bagging 84.52% TSPYL5
Naïve Bayes 84.52% TSPYL5
Naïve Bayes with boosting 84.52% TSPYL5
Naïve Bayes with bagging 88.69% TSPYL5-DIAPH1-NMU
LMT 84.52% TSPYL5
NBTree 84.52% TSPYL5
Random Forest 84.52% TSPYL5-DIAPH1-ASPM
Random Forest with boosting 84.52% TSPYL5-DIAPH1-ASPM
Random Forest with bagging 88.69% TSPYL5-DIAPH1-ASPM-NMU
k-NN 80.36% TSPYL5
Logistic Regression 81.55% TSPYL5-DIAPH1-CA9
ANN 77.38% TSPYL5-CA9
SVM 83.33% TSPYL5-LIN9
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