A Noise Tolerant Fine Tuning Algorithm for the Naïve Bayesian learning Algorithm

Journal Article

Khalil, El-Hindi . 2014

• Publication Online URL: Available online 19 May 2014
• Magazine \ Newspaper: Journal of King Saud University - Computer and Information Sciences, Elsevier.
• Issue Number: 2
• Volume Number: 26

Publication Abstract

This work improves on the FTNB algorithm to make it more tolerant of noise. The FTNB algorithm augments the Naïve Bayesian (NB) learning algorithm with a fine tuning stage in an attempt to find better estimations of the probability terms involved. The fine tuning stage has proved to be effective in improving the classification accuracy of the NB, however, it makes the NB algorithm more sensitive to noise in a training set.  This work presents several modifications of the fine turning stage in order to make it more tolerant of noise. Our empirical results using 47 data sets show that the proposed methods greatly enhance the algorithms tolerance of noise. Furthermore, one of the proposed methods improved the performance of fine tuning method on many noise free data sets.