João Gama is an associate professor and senior researcher in the Laboratory of Artificial Intelligence and Decision Support (LIAAD) at the University of Porto in Portugal.

… 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, 2012Gama 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

• Knowledge Discovery from Data Streams. Introduction to Data Streams. Change Detection. Maintaining Histograms from Data Streams. Evaluating Streaming Algorithms. Clustering from Data Streams. Frequent Pattern Mining. Decision Trees from Data Streams. Novelty Detection in Data Streams. Ensembles of Classifiers. Time Series Data Streams. Ubiquitous Data Mining. Final Comments. Appendix. Bibliography. Index.

João Gama is an associate professor and senior researcher in the Laboratory of Artificial Intelligence and Decision Support (LIAAD) at the University of Porto in Portugal.

… 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, 2012Gama 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

• Knowledge Discovery from Data Streams. Introduction to Data Streams. Change Detection. Maintaining Histograms from Data Streams. Evaluating Streaming Algorithms. Clustering from Data Streams. Frequent Pattern Mining. Decision Trees from Data Streams. Novelty Detection in Data Streams. Ensembles of Classifiers. Time Series Data Streams. Ubiquitous Data Mining. Final Comments. Appendix. Bibliography. Index.

João Gama is an associate professor and senior researcher in the Laboratory of Artificial Intelligence and Decision Support (LIAAD) at the University of Porto in Portugal.

… 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, 2012Gama 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

• Knowledge Discovery from Data Streams. Introduction to Data Streams. Change Detection. Maintaining Histograms from Data Streams. Evaluating Streaming Algorithms. Clustering from Data Streams. Frequent Pattern Mining. Decision Trees from Data Streams. Novelty Detection in Data Streams. Ensembles of Classifiers. Time Series Data Streams. Ubiquitous Data Mining. Final Comments. Appendix. Bibliography. Index.