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

Description: Data Mining Algorithms in C++ by Timothy Masters 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 Youll LearnUse Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your dataDiscover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the dataWork with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methodsSee how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the dataPlot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is highWho This Book Is ForAnyone 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Back Cover 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, youll 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 Author Biography 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 hes been involved in the development of automated trading systems in various financial markets. Table of Contents 1. Information and Entropy.- 2. Screening for Relationships.- 3. Displaying Relationship Anomalies.- 4. Fun With Eigenvectors.- 5. Using the DATAMINE Program. Feature An expert-driven data mining and algorithms in C++ book Data mining is an important topic in big data Algorithms are also a critical topic of growing importance Details ISBN148423314X Year 2017 ISBN-10 148423314X ISBN-13 9781484233146 Format Paperback Edition 1st Imprint APress Place of Publication Berkley Country of Publication United States Author Timothy Masters DEWEY 005.11 Subtitle Data Patterns and Algorithms for Modern Applications Pages 286 Publication Date 2017-12-19 Short Title Data Mining Algorithms in C++ Language English UK Release Date 2017-12-19 AU Release Date 2017-12-19 NZ Release Date 2017-12-19 US Release Date 2017-12-19 Illustrations XIV, 286 p. Narrator Paul Panting Edited by Jeffrey Insko Birth 1945 Affiliation Georgia Institute of Technology Position Kranzberg Professor Qualifications J.D. Publisher APress Edition Description 1st ed. Alternative 9781484247112 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:117488257;

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