Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page 8
... parameters that are to be determined from data for the chosen function using the particular representational form or tool . • The preference criterion : A basis for preference of one model or set of parameters over another , depending ...
... parameters that are to be determined from data for the chosen function using the particular representational form or tool . • The preference criterion : A basis for preference of one model or set of parameters over another , depending ...
Page 250
... parameters corresponding to the c medoids , with the parameter values corresponding to their record IDs in the database . The strings are not binary , as in conventional GAs ( Section 2.2.5 ) , but consist of integer values lying ...
... parameters corresponding to the c medoids , with the parameter values corresponding to their record IDs in the database . The strings are not binary , as in conventional GAs ( Section 2.2.5 ) , but consist of integer values lying ...
Page 308
... parameters are also tuned . The initial population consists of all possible net- works generated from rough set theoretic rules . As explained in Section 2.2.5 , GAs involve three basic procedures , namely , ( i ) encoding of the ...
... parameters are also tuned . The initial population consists of all possible net- works generated from rough set theoretic rules . As explained in Section 2.2.5 , GAs involve three basic procedures , namely , ( i ) encoding of the ...
Contents
Soft Computing | 37 |
Multimedia Data Compression | 89 |
standard | 129 |
Copyright | |
9 other sections not shown
Other editions - View all
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya Limited preview - 2005 |
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya No preview available - 2005 |
Common terms and phrases
applications approach association rules ATATA binary Bioinformatics Boyer-Moore algorithm C₁ categorical classification clustering coding coefficients color components computational complexity content-based image retrieval corresponding data compression data mining database dataset decision tree decoder defined dictionary distance document domain efficient encoder outputs entropy entropy encoding evaluation example extracted feature fuzzy sets gene Hence Huffman code IEEE Transactions image retrieval initial input integer involving JPEG Karp-Rabin knowledge discovery knowledge-based network learning length linguistic matching algorithms matrix measure method mismatch Mitra multimedia data neural networks neuro-fuzzy neurons objects occurrence optimal partition pattern matching pixel prediction prefix protein pruning quantization query represented result rough set sample Section sequence shown in Fig soft computing split statistical string matching structure substring suffix symbol Table techniques text mining transformed vector wavelet Web mining weights