Bayes and Tree Classifiers for File Classification |
Author(s): |
| Dr. S.Vijayarani , Bharathiar University; J,Ilamathi, Bharathiar University |
Keywords: |
| Classification, Bayes, Naïve Bayes Updatable, REP tree |
Abstract |
|
This research work primarily focuses on classifying the files which are stored in the computer system based on their extension (.pdf, .jpg, .docx, .txt, and .png). The aim of this work is to analyze the performance of two different classification algorithms. Two types of classification algorithms used and tested in this work are Naïve Bayes Updatable for Bayes modeling and REP tree (Reduced Error Pruning Tree) classification algorithm for Tree modeling. From the experimental results, it is observed that the REP tree classifier performance is better than the Naïve Bayes Updatable classifier. The performance factors used are classification accuracy and error rate. This work is carried out in WEKA data mining tool. |
Other Details |
|
Paper ID: IJSRDV3I1708 Published in: Volume : 3, Issue : 1 Publication Date: 01/04/2015 Page(s): 1409-1412 |
Article Preview |
|
|
|
|
