автор: Dan A. Simovici

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general …

This volume was born from the experience of the authors as researchers and educators, whichsuggeststhatmanystudentsofdataminingarehandicapped in their research by the lack of a formal, systematic …

Mathematical Foundations of Computer Science, Volume I is the first of two volumes presenting topics from mathematics (mostly discrete mathematics) which have proven relevant and useful to computer …

This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical …

This unique compendium gives an updated presentation of clustering, one of the most challenging tasks in machine learning. The book provides a unitary presentation of classical and contemporary …

This updated compendium provides the linear algebra background necessary to understand and develop linear algebra applications in data mining and machine learning. Basic knowledge and advanced new …

Logic is a foundational mathematical discipline for Computer Science. This unique compendium provides the main ideas and techniques originating from logic. It is divided into two volumes — propositio …