Researchers and Professionals in data mining and related fields should be familiar with different models and standard algorithms in use to have a clear understanding of the concepts involved. Data Mining Algorithms provides the reader with unprecedented insights into the working of various algorithms. Several novel algorithms in association rules, decision trees, statistics, information retrieval etc are clearly defined, and thoroughly discussed. The well-known page rank metric used by search engines is extended in multiple ways in chapter 5 to improve the quality of search results. A highly informative discussion of support vector machines appears in chapter 6. Students in data mining, machine learning, soft computing and statistics will find a wealth of useful and reliable information in this unique and indispensable volume. Scientists, engineers, senior undergraduate and graduate students in applied sciences will all find this book to be extremely useful to sharpen their skills, to improve their general knowledge, and to explore the computational aspects of complex models and algorithms presented.

• • Thorough discussion of many novel algorithms • Numerical examples that illustrate the models and algorithms • Up-to-date information on the advances in the literature • A fairly comprehensive list of references at the end of each chapter • Examples drawn from a wide variety of fields • A large number of exercises with solutions to selected exercises

Introduction to Data Mining / Probability and Statistics / Decision Trees / Association Rules / Web Mining / Support Vector Machines / Latent Semantic Indexing / Spatial Data Mining / Appendixes / Author Index / Subject Index.

Postgraduate Students, Professionals, Researchers and Industry