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Data mining algorithms in C++data pa...

Masters, Timothy.

Data mining algorithms in C++data patterns and algorithms for modern applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data mining algorithms in C++by Timothy Masters.
Reminder of title:	data patterns and algorithms for modern applications /
Author:	Masters, Timothy.
Published:	Berkeley, CA :Apress :2018.
Description:	xiv, 286 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Data mining.
Online resource:	http://dx.doi.org/10.1007/978-1-4842-3315-3
ISBN:	9781484233153$q(electronic bk.)

Data mining algorithms in C++data patterns and algorithms for modern applications /
Masters, Timothy.

Data mining algorithms in C++data patterns and algorithms for modern applications /[electronic resource] :by Timothy Masters. - Berkeley, CA :Apress :2018. - xiv, 286 p. :ill., digital ;24 cm.

1. Information and Entropy -- 2. Screening for Relationships -- 3. Displaying Relationship Anomalies -- 4. Fun With Eigenvectors -- 5. Using the DATAMINE Program.

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.

ISBN: 9781484233153$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-3315-3doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data mining algorithms in C++data patterns and algorithms for modern applications /
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245 1 0 $a Data mining algorithms in C++ $h [electronic resource] : $b data patterns and algorithms for modern applications / $c by Timothy Masters.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a xiv, 286 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1. Information and Entropy -- 2. Screening for Relationships -- 3. Displaying Relationship Anomalies -- 4. Fun With Eigenvectors -- 5. Using the DATAMINE Program.
520 $a 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.
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650 0 $a Computer algorithms. $3 184478
650 0 $a C++ (Computer program language) $3 181958
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650 2 4 $a Big Data. $3 760530
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Programming Techniques. $3 274470
650 2 4 $a Algorithms. $3 184661
710 2 $a SpringerLink (Online service) $3 273601
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950 $a Professional and Applied Computing (Springer-12059)