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Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields including biology and medicine. However, biomedical researchers often experience difficulties grasping both the theory and applications of these important methods because of lack of technical background. The purpose of this book is to introduce SVMs and their extensions and allow biomedical researchers to understand and apply them in real-life research in a very easy manner. The book is to consist of two volumes: theory and methods (Volume 1) and case studies (Volume 2).
Readership: Biomedical researchers and healthcare professionals who would like to learn about SVMs and relevant bioinformatics tools but do not have the necessary technical background.
- Sales Rank: #3250029 in Books
- Published on: 2013-05-06
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 7.75" w x .75" l, .0 pounds
- Binding: Hardcover
- 212 pages
Review
"The authors make a worthy contribution to the informatics in the biomedicine field by introducing various biomedicine applications for which SVM can be used successfully. The potentials of SVM in biomedicine are addressed in a well-written, rigorous, and engaging manner; therefore, readers gain a comprehensive perspective on the use of SVM in biomedicine applications that will add to their own bank of knowledge." -- Dr Ulas Bagci, National Institutes of Health, Maryland, USA
From the Inside Flap
Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields including biology and medicine. However, biomedical researchers often experience difficulties grasping both the theory and applications of these important methods because of lack of technical background. The purpose of this book is to introduce SVMs and their extensions and allow biomedical researchers to understand and apply them in real-life research in a very easy manner. The book is to consist of two volumes: theory and methods (Volume 1) and cases studies (Volume 2).
The proposed book follows the approach of "programmed learning" whereby material is presented in short sections called "frames." Each frame consists of a very small amount of information to be learned, a multiple choice quiz, and answers to the quiz. The reader can proceed to the next frame only after verifying the correct answers to the current frame.
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