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the data mining process. An overview of useful business applications is
provided.
Chapter 2 presents the data mining process in more detail. It demonstrates
this process with a typical set of data. Visualization of data through data
mining software is addressed.
Chapter 3 presents memory-based reasoning methods of data mining.
Major real applications are described. Algorithms are demonstrated with
prototypical data based on real applications.
Chapter 4 discusses association rule methods. Application in the form of
market basket analysis is discussed. A real data set is described, and a simplified
version used to demonstrate association rule methods.
Chapter 5 presents fuzzy data mining approaches. Fuzzy decision tree approaches
are described, as well as fuzzy association rule applications. Real
data mining applications are described and demonstrated
Chapter 6 presents Rough Sets, a recently popularized data mining method.
Chapter 7 describes support vector machines and the types of data sets in
which they seem to have relative advantage.
Chapter 8 discusses the use of genetic algorithms to supplement various
data mining operations.
Chapter 9 describes methods to evaluate models in the process of data
mining.
Chapter 10 presents a spectrum of successful applications of the data mining
techniques, focusing on the value of these analyses to business decision
making.
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