Knowledge Discovery from Data Streams

... this book is the first authored text (that is, not an edited collection) about the area ... The book covers a lot of ground in just 200 pages, including discussion of relatively advanced methods such as wavelets, bagging, boosting, dynamic time warping, and symbolic representation of time series. There is also, I was pleased to see, a chapter on evaluating streaming algorithms ... . Evaluation, in general, deserves more attention than it generally receives, so I was delighted to see the focus on it here. ... a good introduction to an area of data analysis which is going to be very important indeed.
-David J. Hand, International Statistical Review, 2012

Gama is one of the leading investigators in the hottest research topic in machine learning and data mining: data streams. ... This book is the first book to didactically cover in a clear, comprehensive and mathematically rigorous way the main machine learning related aspects of this relevant research field. ... an up-to-date, broad and useful source of reference for all those interested in knowledge acquisition by learning techniques.
-From the Foreword by André Ponce de Leon Ferreira de Carvalho, University of São Paulo, Brazil