Abstract
The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their data and can help in building classification models. This presentation will introduce the techniques for contrasting data sets. It will also focus on some important real world applications that illustrate how contrast patterns can be applied effectively for building robust classifiers.
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© 2010 Springer-Verlag Berlin Heidelberg
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Ramamohanarao, K. (2010). Contrast Pattern Mining and Its Application for Building Robust Classifiers. In: Hutter, M., Stephan, F., Vovk, V., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 2010. Lecture Notes in Computer Science(), vol 6331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16108-7_5
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DOI: https://doi.org/10.1007/978-3-642-16108-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16107-0
Online ISBN: 978-3-642-16108-7
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