Summary
Within this chapter, I gave you an overview of data mining and the various types of descriptive and predictive data modeling tasks in order to give you some perspective as to how you can put parsed or extracted data to work for you. I also covered several Perl modules that you may find beneficial when programming data mining routines. However, it is notable that the field of data mining is still in a developmental stage, and many areas of data mining exist for which applicable Perl utilities have not yet been developed. Finally, the chapter briefly introduced machine learning via a feed-forward neural network that was trained to solve the XOR problem. Although the XOR example is a far cry from a modern data mining neural network, the example illustrates the basic principles of machine learning.
This chapter concludes the Pro Perl Parsing book, but I hope you view it not as an ending but rather as a step toward gaining the skills necessary to successfully navigate the momentous volumes of data being generated in this information age. Happy hacking.
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© 2005 Christopher M. Frenz
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(2005). Performing Text and Data Mining. In: Pro Perl Parsing. Apress. https://doi.org/10.1007/978-1-4302-0049-9_10
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DOI: https://doi.org/10.1007/978-1-4302-0049-9_10
Publisher Name: Apress
Print ISBN: 978-1-59059-504-6
Online ISBN: 978-1-4302-0049-9
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