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Machine learning with svm and other kernal methods (Record no. 7421)

MARC details
000 -LEADER
fixed length control field 02078nam a2200229 a 4500
001 - CONTROL NUMBER
control field ASIN8120334353
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190522131157.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 141029s2009 xxu eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 8120334353 (paperback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788120334359 (paperback)
037 ## - SOURCE OF ACQUISITION
Terms of availability 822.00 PKR
040 ## - CATALOGING SOURCE
Transcribing agency AUI
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Soman, K. P.
9 (RLIN) 4539
245 10 - TITLE STATEMENT
Title Machine learning with svm and other kernal methods
Statement of responsibility, etc. K. P. Soman, R. Loganathan.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New Delhi
Name of publisher, distributor, etc. Prentice-Hall of India Pvt.Ltd,
Date of publication, distribution, etc. 2009.
300 ## - PHYSICAL DESCRIPTION
Extent xviii; 477 p.
Dimensions 24 cm.
520 ## - SUMMARY, ETC.
Summary, etc. Support vector machines (SVMs) represent a breakthrough in the theory of learning systems. It is a new generation of learning algorithms based on recent advances in statistical learning theory. Designed for the undergraduate students of computer science and engineering, this book provides a comprehensive introduction to the state-of-the-art algorithm and techniques in this field. It covers most of the well known algorithms supplemented with code and data. One Class, Multiclass and hierarchical SVMs are included which will help the students to solve any pattern classification problems with ease and that too in Excel. This title includes extensive coverage of Lagrangian duality and iterative methods for optimization; separate chapters on kernel based spectral clustering, text mining, and other applications in computational linguistics and speech processing; a chapter on latest sequential minimization algorithms and its modifications to do online learning; step-by-step method of solving the SVM based classification problem in Excel; and, kernel versions of PCA, CCA and ICA. The CD accompanying this book includes animations on solving SVM training problem in Microsoft EXCEL and by using SVMLight software. In addition, Matlab codes are given for all the formulations of SVM along with the data sets mentioned in the exercise section of each chapter.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Loganathan, R.
9 (RLIN) 4540
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Amazon.com
Uniform Resource Identifier <a href="http://www.amazon.com/exec/obidos/ASIN/8120334353/chopaconline-20">http://www.amazon.com/exec/obidos/ASIN/8120334353/chopaconline-20</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Inventory number Total Checkouts Full call number Barcode Date last seen Date last checked out Cost, replacement price Price effective from Koha item type Public note
    Dewey Decimal Classification       Air University Central Library Islamabad Air University Central Library Islamabad Computer Science 10/29/2014 Allied Book Company 0498 3 006.3105195 SOM P9721 11/29/2019 10/24/2019 822.00 06/25/2012 Book Program Relevancy: BSCS; Course Relevancy: Machine Learning; Artificial Intelligence
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