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PHP probability models for Web Data
Posted by Philipp Esselbach on: 10/08/2003 04:57 PM [ Print | 0 comment(s) ]
A good example of using a probability model to solove a serious problem is the SpamBayes filtering engine, which uses machine learning and Bayesian inference techniques to compute the probability that a given piece of e-mail is spam. This article demonstrates how to develop univariate probability models in PHP; discusses how to fit empirical data distributions to a theoretical probability distribution; and showcases an important tool for all this -- the Probability Distributions Library (PDL).