Naïve Bayes Classifier with Various Smoothing Techniques for Text Documents
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - April Issue 2013 by IJCTT Journal|
|Volume-4 Issue-4 |
|Year of Publication : 2013|
|Authors :Shruti Aggarwal, Devinder Kaur|
Shruti Aggarwal, Devinder Kaur "Naïve Bayes Classifier with Various Smoothing Techniques for Text Documents "International Journal of Computer Trends and Technology (IJCTT),V4(4):873-876 April Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: -Due to huge amount of increase in text data, its classification has become an important issue, now days. There are many good classification techniques discussed in this paper. Each classification method has its own assumptions, advantages and limitations. One of the most widely used classifier is Naïve Bayes which performs well with different data sets. Various Smoothing techniques are applied on Naïve Bayes. The idea behind them is to improve the classification accuracy and performance.
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Keywords —Text classification, Naïve Bayes, Jelinek-Mercer, Smoothing, Dirichlet, Two-Stage, Absolute Discounting