| Title : | Pattern recognition | | Material Type: | printed text | | Authors: | Sergios Theodoridis, Author ; Konstantinos Koutroumbas, Author | | Edition statement: | 4th ed. | | Publisher: | Elsevier/Academic Press, (Amsterdam -London) | | Publication Date: | 2009 | | Pagination: | xvii, 961 p. | | Layout: | ill. | | Size: | 25 cm | | ISBN (or other code): | 978-1-597-49272-0 | | General note: | Includes bibliographical references and index | | Languages : | English (eng) Original Language : English (eng) | | Descriptors: | Pattern recognition systems - Data processing
| | Class number: | 006.4 | | Abstract: | "Pattern recognition" - this book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition : semi-supervised learning, combining clustering algorithms, and relevance feedback. Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques. Many more diagrams included--now in two color--to provide greater insight through visual presentation· Matlab code of the most common methods are given at the end of each chapter. More Matlab code is available, together with an accompanying manual, via this site. Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms. | | Contents note: | Introduction; Classifiers based on bayes decision; Linear classifiers; Nonlinear classifiers; Feature selection; Feature generation I : Data transformation and dimensionality reduction; Feature generation II; Template matching; Context depedant Clarification; System evaluation; Clustering : Basic concepts; Clustering algorithms : algorithms L sequential; Clustering algorithms II : Hierarchical; Clustering algorithms III : Based on function optimization; Clustering algorithms IV : Clustering; Cluster validity; | | Record link: | https://library.seeu.edu.mk/index.php?lvl=notice_display&id=13887 |
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