|
Class for building and using a Complement class Naive Bayes classifier.
For more information see,
Jason D. Rennie, Lawrence Shih, Jaime Teevan, David R. Karger: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: ICML, 616-623, 2003.
P.S.: TF, IDF and length normalization transforms, as described in the paper, can be performed through weka.filters.unsupervised.StringToWordVector.
BibTeX:
@inproceedings{Rennie2003,
author = {Jason D. Rennie and Lawrence Shih and Jaime Teevan and David R. Karger},
booktitle = {ICML},
pages = {616-623},
publisher = {AAAI Press},
title = {Tackling the Poor Assumptions of Naive Bayes Text Classifiers},
year = {2003}
}
Valid options are:
-N
Normalize the word weights for each class
-S
Smoothing value to avoid zero WordGivenClass probabilities (default=1.0).
author:
Ashraf M. Kibriya (amk14@cs.waikato.ac.nz)
version:
$Revision: 1.8 $ |
