Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page 56
... chromosome to represent real values of the vari- ables x , with the length of the vector depending on the required precision . A population is a set of individuals ( chromosomes ) representing the concate- nated parameter set X1 , X2 ...
... chromosome to represent real values of the vari- ables x , with the length of the vector depending on the required precision . A population is a set of individuals ( chromosomes ) representing the concate- nated parameter set X1 , X2 ...
Page 57
... chromosome . Decoding is the reverse of encoding . For a continuous - valued parameter the binary representation is converted to a continuous value by the expression lower bound + i = 0 bits_used - 1 bit ; * 2i 2bits_used 1 ...
... chromosome . Decoding is the reverse of encoding . For a continuous - valued parameter the binary representation is converted to a continuous value by the expression lower bound + i = 0 bits_used - 1 bit ; * 2i 2bits_used 1 ...
Page 58
... chromosome pair is selected for crossover . Again , crossover can be one point , two point , multipoint , or uniform . Let us consider , as an example , two parent chromosomes xyxyxyxy and abababab where x , y , a , b are binary . In ...
... chromosome pair is selected for crossover . Again , crossover can be one point , two point , multipoint , or uniform . Let us consider , as an example , two parent chromosomes xyxyxyxy and abababab where x , y , a , b are binary . In ...
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