Additional file 14.
Description of classifiers and classifier performance evaluators used in the study. Brief descriptions of the Naïve Bayes, Logistic Regression, Random Forests and ZeroR classifiers along with the feature selection algorithms used (Information Gain and Cfs Subset evaluator) are given. Mathematical formulas for true and false positive and negative rates (classifier evaluation metrics) are also provided.
Format: DOC Size: 35KB Download file
This file can be viewed with: Microsoft Word Viewer
Ghosh et al. BMC Medical Genomics 2010 3:56 doi:10.1186/1755-8794-3-56