Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/720
Title: Data Mining Algorithms in C++
Other Titles: Data Patterns and Algorithms for Modern Applications /
Authors: Masters, Timothy. ;
subject: Computer Science;Computer Programming;Programming Languages and Electronic Computers;Data Mining;Algorithms;Computer Science;Programming Languages and Compilers and Interpreters;Big Data. ;;Data Mining and Knowledge Discovery;Programming Techniques;Algorithms;005.13 ; 23 ;;QA76.76.C65 ;
Year: 2018
place: Berkeley, CA :
Publisher: Apress :
Imprint: Apress,
Abstract: 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,eData Mining Algorithms in C++eincludes 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. e 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 programe. ;
Description: 
Printed edition: ; 9781484233146. ;
SpringerLink (Online service) ;



URI: http://localhost/handle/Hannan/720
ISBN: 9781484233153 ;
9781484233146 (print) ;
More Information: XIV, 286 p. 26 illus., 8 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

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Title: Data Mining Algorithms in C++
Other Titles: Data Patterns and Algorithms for Modern Applications /
Authors: Masters, Timothy. ;
subject: Computer Science;Computer Programming;Programming Languages and Electronic Computers;Data Mining;Algorithms;Computer Science;Programming Languages and Compilers and Interpreters;Big Data. ;;Data Mining and Knowledge Discovery;Programming Techniques;Algorithms;005.13 ; 23 ;;QA76.76.C65 ;
Year: 2018
place: Berkeley, CA :
Publisher: Apress :
Imprint: Apress,
Abstract: 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,eData Mining Algorithms in C++eincludes 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. e 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 programe. ;
Description: 
Printed edition: ; 9781484233146. ;
SpringerLink (Online service) ;



URI: http://localhost/handle/Hannan/720
ISBN: 9781484233153 ;
9781484233146 (print) ;
More Information: XIV, 286 p. 26 illus., 8 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484233146.pdf3.74 MBAdobe PDFThumbnail
Preview File
Title: Data Mining Algorithms in C++
Other Titles: Data Patterns and Algorithms for Modern Applications /
Authors: Masters, Timothy. ;
subject: Computer Science;Computer Programming;Programming Languages and Electronic Computers;Data Mining;Algorithms;Computer Science;Programming Languages and Compilers and Interpreters;Big Data. ;;Data Mining and Knowledge Discovery;Programming Techniques;Algorithms;005.13 ; 23 ;;QA76.76.C65 ;
Year: 2018
place: Berkeley, CA :
Publisher: Apress :
Imprint: Apress,
Abstract: 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,eData Mining Algorithms in C++eincludes 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. e 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 programe. ;
Description: 
Printed edition: ; 9781484233146. ;
SpringerLink (Online service) ;



URI: http://localhost/handle/Hannan/720
ISBN: 9781484233153 ;
9781484233146 (print) ;
More Information: XIV, 286 p. 26 illus., 8 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484233146.pdf3.74 MBAdobe PDFThumbnail
Preview File