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Table 3 Correctly classified proteins by Weka algorithms

From: ProClaT, a new bioinformatics tool for in silico protein reclassification: case study of DraB, a protein coded from the draTGB operon in Azospirillum brasilense

Algorithm Options Correctly classified instances without cross-validation Correctly classified instances with cross-validation
Multilayer Perceptron -L 0.3 –M 0.2 –N 500 –V 0 –S 0 –E 20 –H a 99.61 % 99.41 %
Simple Cart -S 1 –M 2.0 –N 5 –C 1.0 99.09 % 99.22 %
Nnge -G 5 –I 5 99.09 % 99.02 %
J48 -C 0.25 –M 2 98.96 % 98.71 %
Ada BoostM1 -P 100 –S 1 –I 0 –W weka.classifiers.trees. DecisionStump 32.51 % 33.35 %
Naive Bayes - 99.22 % 98.90 %
  1. Using the default parameters proposed by Weka, the neural network training and test files were submitted to the six algorithms above. MLPNN showed the best number of correctly classified proteins