Data Mining Algorithms in C++

Data Patterns and Algorithms for Modern Applications

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Éditeur :

Apress


Paru le : 2017-12-15



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Description

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

Use Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your data
Discover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the data
Work with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methods
See how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the data
Plot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is high



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.
Pages
286 pages
Collection
n.c
Parution
2017-12-15
Marque
Apress
EAN papier
9781484233146
EAN PDF
9781484233153

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
28
Taille du fichier
4731 Ko
Prix
78,87 €
EAN EPUB
9781484233153

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
28
Taille du fichier
1997 Ko
Prix
78,87 €

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