This document discusses Hadoop, HBase, Mahout, naive Bayes classification, and analyzing web content. It provides an example of using Mahout to train a naive Bayes classifier on web content stored in Hadoop and HBase. Evaluation results are presented, showing over 90% accuracy in classifying different types of web content. The effects of parameters like alpha values, n-grams, and feature selection
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