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{ "item_title" : "Pattern Recognition", "item_author" : [" Konstantinos Koutroumbas", "Sergios Theodoridis "], "item_description" : "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.- An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/59/749/272/1597492728_b.jpg", "price_data" : { "retail_price" : "109.00", "online_price" : "109.00", "our_price" : "109.00", "club_price" : "109.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Pattern Recognition|Konstantinos Koutroumbas

Pattern Recognition

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Overview

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.
- An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).

This item is Non-Returnable

Details

  • ISBN-13: 9781597492720
  • ISBN-10: 1597492728
  • Publisher: Academic Press
  • Publish Date: September 2008
  • Dimensions: 9.3 x 7.6 x 2 inches
  • Shipping Weight: 4.05 pounds
  • Page Count: 984

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