© 2018

Data Mining Algorithms in C++

Data Patterns and Algorithms for Modern Applications


Table of contents

  1. Front Matter
    Pages i-xiv
  2. Timothy Masters
    Pages 1-73
  3. Timothy Masters
    Pages 75-166
  4. Timothy Masters
    Pages 167-184
  5. Timothy Masters
    Pages 185-265
  6. Timothy Masters
    Pages 267-279
  7. Back Matter
    Pages 281-286

About this book


Find the various relationships among variables that can be present in big data as well as other data sets. This book also covers information entropy, permutation tests, combinatorics, predictor selections, and eigenvalues to give you a well-rounded view of data mining and algorithms in C++.

Furthermore, Data Mining Algorithms in C++ includes classic techniques that are widely available in standard statistical packages, such as maximum likelihood factor analysis and varimax rotation. After reading and using this book, you'll come away with many code samples and routines that can be repurposed into your own data mining tools and algorithms toolbox. This will allow you to integrate these techniques in your various data and analysis projects.  

You will:
  • Discover useful data mining techniques and algorithms using the C++ programming language
  • Carry out permutation tests
  • Work with the various relationships and screening types for these relationships
  • Master predictor selections
  • Use the DATAMINE program 


Data Mining big data algorithms C++ programming mining software code technique

Authors and affiliations

  1. 1.IthacaUSA

About the authors

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.

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