Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications

Discover hidden relationships among the variables in your data, and learn how to exploit these relationships.  This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications.  All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code.

Many of these techniques are recent developments, still not in widespread use.  Others are standard algorithms given a fresh look.  In every case, the focus is on practical applicability, with all code written in such a way that it can easily be included into any program.  The Windows-based DATAMINE program lets you experiment with the techniques before incorporating them into your own work.

What You'll Learn

Who This Book Is For

Anyone interested in discovering and exploiting relationships among variables.  Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.

Timothy Masters has a PhD in statistics and is an experienced programmer.  His dissertation was in image analysis.  His career moved in the direction of signal processing, and for the last 25 years he's been involved in the development of automated trading systems in various financial markets.