LEADER 03671oam 2200769I 450 001 9910817159803321 005 20200520144314.0 010 $a9780429109782 010 $a0429109784 010 $a9781439862247 010 $a1439862249 024 7 $a10.1201/b10814 035 $a(CKB)2550000000065024 035 $a(EBL)800964 035 $a(OCoLC)740901290 035 $a(SSID)ssj0000514886 035 $a(PQKBManifestationID)11358557 035 $a(PQKBTitleCode)TC0000514886 035 $a(PQKBWorkID)10523683 035 $a(PQKB)11553678 035 $a(Au-PeEL)EBL800964 035 $a(CaPaEBR)ebr10511315 035 $a(CaONFJC)MIL692626 035 $a(OCoLC)759865957 035 $a(CaSebORM)9781439862247 035 $a(MiAaPQ)EBC800964 035 $a(PPN)171290550 035 $a(OCoLC)861618525 035 $a(OCoLC)ocn861618525 035 $a(OCoLC)892786087 035 $a(FINmELB)ELB155173 035 $a(EXLCZ)992550000000065024 100 $a20180331d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aData clustering in C++ $ean object-oriented approach /$fGuojun Gan 205 $a1st edition 210 $aBoca Raton $cCRC Press$d2011 210 1$aBoca Raton, Fla. :$cChapman and Hall/CRC,$d2011. 215 $a1 online resource (512 p.) 225 1 $aChapman & Hall/CRC data mining and knowledge discovery series 300 $aA Chapman & Hall book. 311 08$a9781322613444 311 08$a1322613443 311 08$a9781439862230 311 08$a1439862230 320 $aIncludes bibliographical references (p. 469-486) and indexes. 327 $aFront Cover; Dedication; Contents; List of Figures; List of Tables; Preface; I. Data Clustering and C++ Preliminaries; 1. Introduction to Data Clustering; 2. The Unified Modeling Language; 3. Object-Oriented Programming and C++; 4. DesignPatterns; 5. C++ Libraries and Tools; II. A C++ Data Clustering Framework; 6. The Clustering Library; 7. Datasets; 8. Clusters; 9. Dissimilarity Measures; 10. Clustering Algorithms; 11. Utility Classes; III. Data Clustering Algorithms; 12. Agglomerative Hierarchical Algorithms; 13. DIANA; 14. The k-means Algorithm; 15. The c-means Algorithm 327 $a16. The k-prototypes Algorithm17. The Genetic k-modes Algorithm; 18. The FSC Algorithm; 19. The Gaussian Mixture Algorithm; 20. A Parallel k-means Algorithm; A. Exercises and Projects; B. Listings; C. Software; Bibliography 330 $aData clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct. Thousands of theoretical papers and a number of books on data clustering have been published over the past 50 years. However, few books exist to teach people how to implement data clustering algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms. Using object-oriented design and programming techniques, Data Clusterin 410 0$aChapman & Hall/CRC data mining and knowledge discovery series. 606 $aCluster analysis$xData processing 606 $aC++ (Computer program language) 615 0$aCluster analysis$xData processing. 615 0$aC++ (Computer program language) 676 $a519.5/3 700 $aGan$b Guojun$f1979,$01667026 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910817159803321 996 $aData clustering in C++$94026619 997 $aUNINA