Chapter 6. Microsoft Naïve Bayes
Picture a newborn witnessing his first sunset. Being new to this world, he doesn't know if the sun will rise again. Making a guess, he gives the chance of a sunrise even odds and places in a bag a black marble, representing no sunrise, and a white marble, representing a sunrise. As each day passes, the child places in the bag a marble based on the evidence he witnesses—in this case, a white marble for each sunrise. Over time, the black marble becomes lost in a sea of white, and the child can say with near certainty that the sun will rise each day.
This was the example posed by Reverend Thomas Bayes in his 1763 paper establishing the methodology that is now one of the fundamental principles of modern machine learning.
In this chapter, you will learn about the following:
How to use the Naïve Bayes algorithm
How to create Naïve Bayes models using DMX
How to interpret Naïve Bayes results
The principles of the Naïve Bayes algorithm
How to tune the Naïve Bayes algorithm using parameters
Examples, data sets, and projects for this chapter may be found in its downloadable companion, Chapter6.zip, which is available on the book's website at www.wiley.com/go/data_mining_SQL_2008/. The archive contains the following:
A SQL Server 2008 database backup containing the data sets used in this chapter
A set of files containing the DMX scripts for this chapter
An Analysis Services project
The DMX examples for this chapter require the database created by deploying the included ...
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