Includes bibliographical references (pages 253-264) and index.
Introduction to Data Mining -- 2 Statistical Methods -- 3 Clustering by k-means -- 4 k-nearest Neighbor Classification -- 5 Artificial Neural Networks -- 6 Support Vector Machines -- 7 Biclustering -- 8 Validation -- 9 An Application in C -- 10 Data Mining in a Parallel Environment -- 11 Solutions of the Exercises -- A. Matlab Environment -- B.C programming language -- C. Message Passing Interface (MPI) -- D. Eigenvalues and Eigenvectors -- References.