20newsgroupClassify in NaiveBayes Matlab

Problem Description: 20 newsgroup Classification problem

Bayesian learning for classifying net news text articles:
Naive Bayes classifiers are among the most successful known algorithms for learning to classify text documents. We will provide a data set containing 20,000 newsgroup messages drawn from the 20 newsgroups. The dataset contains 1000 documents from each of the 20 newsgroups.

1. For classes descriptions, please refer Table 6.3 of Dr. Mitchell’s book (Machine Learning, Tom Mitchell)

2. Please download the data from http://www.cs.cmu.edu/afs/cs/project/theo-11/www/naive-bayes.html
Report: A Comprehensive Report below: “20 newsgroup Classification problem”
Accuracy: 83.625%
Number of Training data: 50% of Total document chosen sequentially
Number of Training data: 50% of remaining document

Download the code and other necessary files in the Files Tab.

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