# developerWorks: Apply Probability Models to Web Data Using PHP

Oct 10, 2003, 08:30 (0 Talkback[s])
(Other stories by Paul Meagher)
"One open source project that has received considerable
attention in the last year is the SpamBayes project, a project that
continues to provide one of the best examples of how probability
theory can inform the design of applications to solve practical
problems. The SpamBayes filtering engine uses machine learning and
Bayesian inference techniques to compute the probability that a
given piece of e-mail is spam.

"This project is also interesting because the main exposure to
software applications of probability theory are generally
math-enabled applications such as statistics programs, and the
project teaches you and me that many fruitful hybrid technologies
can result from the cross-fertilization of traditional application
domains with ideas and techniques from probability theory. To
utilize such cross-fertilization, it is not necessary to learn
advanced aspects of probability theory; some of the most elementary
aspects of probability theory could be used today to inform the
design of your next application.

"In this article, I introduce you to some of the most basic
concepts, techniques, and tools that define the area of probability
modeling, focusing in particular on the role played by probability
distributions in constructing univariate probability models. So you
are able to use these concepts in practice, I will show you how to
develop univariate probability models that are completely
implemented in the popular and easy-to-use scripting language PHP.
But the concepts are universal enough so that those who prefer
other scripting languages will be able to understand and learn from
the implementations as well..."

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