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Data Mining pp 185-317 | Cite as

Data Mining Techniques and Models

  • Florin Gorunescu
Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 12)

Abstract

Data mining can also be viewed as a process of model building, and thus the data used to build the model can be understood in ways that we may not have previously taken into consideration. This chapter summarizes some well-known data mining techniques and models, such as: Bayesian classifier, association rule mining and rule-based classifier, artificial neural networks, k-nearest neighbors, rough sets, clustering algorithms, and genetic algorithms. Thus, the reader will have a more complete view on the tools that data mining borrowed from different neighboring fields and used in a smart and efficient manner for digging in data for hidden knowledge.

Keywords

Genetic Algorithm Support Vector Machine Association Rule Gaussian Mixture Modeling Travel Salesman Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Florin Gorunescu

    There are no affiliations available

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