Stream Data Mining: Algorithms and Their Probabilistic Properties

Presents a unique approach to stream data mining

Contrary to the vast majority of previous approaches, mainly based on some heuristics, this book shows methods and algorithms which are mathematically justified

Designed for a professional audience composed of researchers and practitioners dealing with stream data (telecommunication, banking, sensor networks)

Presents a unique and innovative approach to stream data mining Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified Is intended for a professional audience composed of researchers and practitioners who deal with stream data (e.g. in telecommunication, banking, and sensor networks)

Résumé
Presents a unique approach to stream data mining

Contrary to the vast majority of previous approaches, mainly based on some heuristics, this book shows methods and algorithms which are mathematically justified

Designed for a professional audience composed of researchers and practitioners dealing with stream data (telecommunication, banking, sensor networks)

Contenu
Introduction and Overview of the Main Results of the Book.- Basic concepts of data stream mining.- Decision Trees in Data Stream Mining.- Splitting Criteria based on the McDiarmid's Theorem.