Data Mining: Multimedia, Soft Computing, and BioinformaticsWhile the digital revolution has made huge volumes of high dimensional multimedia data available, it has also challenged users to extract the information they seek from heretofore unthinkably huge datasets. Traditional hard computing data mining techniques have concentrated on flat-file applications. Soft computing tools - such as fuzzy sets, artificial neural networks, genetic algorithms and rough sets - however, offer the opportunity to apply a wide range of data types to a variety of vital functions by handling real-life uncertainty with low-cost solutions. "Data Mining: Multimedia, Soft Computing, and Bioinformatics" provides an accessible introduction to fundamental and advanced data mining technologies. |
From inside the book
Results 1-3 of 72
Page 46
... domain . For example , consider the case of supervised classification . Here a pattern is characterized by a number of features , each taking up different weights in characterizing the classes . A multilayer perceptron in which the ...
... domain . For example , consider the case of supervised classification . Here a pattern is characterized by a number of features , each taking up different weights in characterizing the classes . A multilayer perceptron in which the ...
Page 59
... domain , which , in turn , may be induced by a given set of attributes ascribed to the objects of the domain . The lower approximation is the set of objects definitely belonging to the vague concept , whereas the up- per approximation ...
... domain , which , in turn , may be induced by a given set of attributes ascribed to the objects of the domain . The lower approximation is the set of objects definitely belonging to the vague concept , whereas the up- per approximation ...
Page 108
... domain to another domain ( usually frequency domain ) is to represent the data in a more compact form in the transformed domain . The optimum transformation also minimizes the mean squared error of the reconstructed image . The Karhunen ...
... domain to another domain ( usually frequency domain ) is to represent the data in a more compact form in the transformed domain . The optimum transformation also minimizes the mean squared error of the reconstructed image . The Karhunen ...
Contents
Soft Computing | 35 |
Multimedia Data Compression | 89 |
standard | 129 |
Copyright | |
8 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 attributes binary Bioinformatics bits C₁ categorical character chromosome classification coding coefficients color components content-based image retrieval corresponding data compression data mining database dataset datatypes decision tree decoder defined dictionary distance document domain encoded entropy entropy encoding evaluation example extracted feature frequent itemsets fuzzy sets gene Hence Huffman code 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 result 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 transformed vector visual wavelet Web mining weights