An introduction to support vector machines : and other kernel-based learning methods / Nello Cristianini and John Shawe-Taylor.
Publisher: Cambridge ; New York : Cambridge University Press, 2000Description: xiii, 189 p. : ill. (some col.) ; 26 cmISBN: 0521780195 (hb)Subject(s): Kernel functions | Support vector machinesDDC classification: 512.52,CRI Online resources: Publisher description | Table of contents
Contents:
The Learning Methodology (Page-1), Linear Learning Machines (Page-9), Kernel Induced Feature Space (Page-26), Generalization Theory (Page-52), Optimization Theory (Page-79), Support Vector Machines (Page-93) implementations Techniques (Page-125), Application of Support Vector Machines Implementations Techniques (Page-149), Pseudo code for the SMO Algorithm (Page-162).
| Item type | Current location | Home library | Shelving location | Call number | URL | Status | Notes | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|---|---|
Reference
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Military College of Signals (MCS) | Military College of Signals (MCS) | Reference | 512.52,CRI (Browse shelf) | Link to resource | Not for loan | Almirah No.19, Shelf No.4 | MCS32728 |
Total holds: 0
The Learning Methodology (Page-1), Linear Learning Machines (Page-9), Kernel Induced Feature Space (Page-26), Generalization Theory (Page-52), Optimization Theory (Page-79), Support Vector Machines (Page-93) implementations Techniques (Page-125), Application of Support Vector Machines Implementations Techniques (Page-149), Pseudo code for the SMO Algorithm (Page-162).
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