Data Mining is an emerging technology that has made its way into science, engineering, commerce and industry as many existing inference methods are obsolete for dealing with massive datasets that get accumulated in data warehouses. This comprehensive and up-to-date text aims at providing the reader with sufficient information about data mining methods and algorithms so that they can make use of these methods for solving real-world problems. The authors have taken care to include most of the widely used methods in data mining with simple examples so as to make the text ideal for classroom learning. To make the theory more comprehensible to the students, many illustrations have been used, and this in turn explains how certain parameters of interest change as the algorithm proceeds. Designed as a textbook for the undergraduate and postgraduate students of computer science, information technology, and master of computer applications, the book can also be used for MBA courses in Data Mining in Business, Business Intelligence, Marketing Research, and Health Care Management. Students of Bioinformatics will also find the text extremely useful. CD-ROM INCLUDE’ The accompanying CD contains Large collection of datasets. Animation on how to use WEKA and ExcelMiner to do data mining.
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. KEY FEATURES 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. Kernel versions of PCA, CCA and ICA The CD accompanying the 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.
IN THIS VOLUME:- IDR Comment – Internal Affairs The Strategic Defence Initiative — Lt Gen EA Vas Limited Nuclear War — Maj Vijay Tiwathia The Role of the Military in Developing Countries — Brig OP Kaushik Counter Measures Against Terrorism — Lt Gen PN Kathpalia Motivation in the Indian Amy – Outgrowing the Colonial Model — Maj GD Bakshi Trust not Technology – Appropriate Weapons Technology for the 1990s — George Rockall Weapons and Technology – Part II — Maj Gurmeet Kanwal Window into Sri Lanka — Dr Manoj Joshi Medical Support of the Ground Forces in NBC Warfare – Part II — Col KP Saksena Punjab - Profile of a Terrorist Movement — IDR Research Team The 155 mm Gun Acquisition — IDR Research Team Unravelling Soviet Military Thought — Brig JS Nagra Teeth to Tail Ratio — Brig Vivek Sapatnekar Changing Dimensions of Himalayan Politics — Dr Harvir Sharma Trends in the Indian Management Scene – Has the Army Anything to Learn — Col JFR Rebello Letter to the Editor – MBT for the 21st Century
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