Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page vii
... Mining 1.11 String Matching 1.12 Bioinformatics 1.13 Data Warehousing 1.14 Applications and Challenges 1.15 Conclusions and Discussion References Contents XV 1 1 5 10 12 14 15 16 18 19 20 21 23 24 25 28 30 vii Contents.
... Mining 1.11 String Matching 1.12 Bioinformatics 1.13 Data Warehousing 1.14 Applications and Challenges 1.15 Conclusions and Discussion References Contents XV 1 1 5 10 12 14 15 16 18 19 20 21 23 24 25 28 30 vii Contents.
Page ix
... applications of Lempel - Ziv coding 139 3.13 Conclusions and Discussion 140 References 140 4 String Matching 143 4.1 Introduction 143 4.1.1 Some definitions and preliminaries 144 4.1.2 String matching problem 146 4.1.3 Brute force ...
... applications of Lempel - Ziv coding 139 3.13 Conclusions and Discussion 140 References 140 4 String Matching 143 4.1 Introduction 143 4.1.1 Some definitions and preliminaries 144 4.1.2 String matching problem 146 4.1.3 Brute force ...
Page xi
... applications 238 6.4.2 Density - based clustering 239 6.4.3 Hierarchical clustering 241 6.4.4 Grid - based methods 243 6.4.5 Other variants 244 Soft Computing - Based Approaches 244 6.5.1 Fuzzy sets 244 6.5.2 Neural networks 246 6.5.3 ...
... applications 238 6.4.2 Density - based clustering 239 6.4.3 Hierarchical clustering 241 6.4.4 Grid - based methods 243 6.4.5 Other variants 244 Soft Computing - Based Approaches 244 6.5.1 Fuzzy sets 244 6.5.2 Neural networks 246 6.5.3 ...
Page xvi
... applications . With the completion of the Human Genome Project , we have access to large databases of biological information . Proper analysis of such huge data , involving decoding of genes in the DNA and the three - dimensional ...
... applications . With the completion of the Human Genome Project , we have access to large databases of biological information . Proper analysis of such huge data , involving decoding of genes in the DNA and the three - dimensional ...
Page xvii
... applications and in Bioinformatics . Chapters 5 to 8 concentrate on classification , clustering , and rule mining . In each of these topics , in addition to the classical discussions that are usually available in the books currently in ...
... applications and in Bioinformatics . Chapters 5 to 8 concentrate on classification , clustering , and rule mining . In each of these topics , in addition to the classical discussions that are usually available in the books currently in ...
Contents
1 | |
2 Soft Computing | 35 |
3 Multimedia Data Compression | 89 |
4 String Matching | 143 |
5 Classification in Data Mining | 181 |
6 Clustering in Data Mining | 227 |
7 Association Rules | 267 |
8 Rule Mining with Soft Computing | 293 |
9 Multimedia Data Mining | 319 |
An Application | 365 |
Index | 392 |
About the Authors | 399 |
Other editions - View all
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya No preview available - 2005 |
Common terms and phrases
analysis applications association rules attributes binary Bioinformatics bits categorical character chromosome classification coding coefficients color components content-based image retrieval corresponding data compression data mining dataset decision tree decoder defined dictionary distance document domain encoded entropy entropy encoding evaluation example extracted feature frequent itemsets fuzzy sets genetic algorithms Hence Huffman code IEEE IEEE Transactions image retrieval initial input interaction involving JPEG knowledge discovery learning linguistic matrix measure method Mitra multimedia data neural networks neuro-fuzzy neurons node objects optimal output parameters partition pattern matching pixel prediction problem protein quantization query representation represented rough set S. K. Pal sample Section sequence shown in Fig soft computing spatial statistical string matching structure subbands subnetworks subsets substring symbol Table techniques text mining Transactions on Neural transformed vector visual wavelet Web mining weights