This book has 1002 Mendeley readers (combined total for all chapters).
Click here to see more details on the Mendeley website.
|Agricultural and Biological Sciences||42||4%|
|Computer and Information Science||24||2%|
|Student > Ph. D. Student||342||34%|
|Student > Master||170||17%|
|Student > Bachelor||59||6%|
|Professor > Associate Professor||45||4%|
The combined chapter downloads for this book are 114,001.
"In this book, we find many ways of representing machine learning from different fields, including active learning, algorithmic learning, case-based learning, classifier systems, clustering algorithms, decision-tree learning, inductive inference, kernel methods, knowledge discovery, multiple-instance learning, reinforcement learning, statistical learning, and support vector machines. Most of the current issues in machine learning research are discussed. … I strongly recommend this book for all researchers interested in the very best of machine learning studies."Agliberto Cierco, ACM Computing Reviews, Vol. 49 (5), 2008