Incremental Discretization for Naive Bayes Learning using FIFFD |
Author(s): |
Mr. Kamal Sutaria , VVP Engineering College, Rajkot Gujarat; Ms. Kruti Khalpada, Nirma University, Ahmedabad, Gujarat; Mr. Kunal Khimani, Gujarat Technological University, Gujarat |
Keywords: |
Discretization, incremental, Naive Bayes. |
Abstract |
Incremental Flexible Frequency Discretization (IFFD) is a recently proposed discretization approach for Naive Bayes (NB). IFFD performs satisfactory by setting the minimal interval frequency for discretized intervals as a fixed number. In this paper, we first argue that this setting cannot guarantee that the selecting MinBinSize is on always optimal for all the different datasets. So the performance of Naive Bayes is not good in terms of classification error. We thus proposed a sequential search method for NB: named Flexible IFFD. Experiments were conducted on 4 datasets from UCI machine learning repository and performance was compared between NB trained on the data discretized by FIFFD, IFFD, and PKID. |
Other Details |
Paper ID: IJSRDV1I3093 Published in: Volume : 1, Issue : 3 Publication Date: 01/06/2013 Page(s): 775-778 |
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