This book has 1109 Mendeley readers (combined total for all chapters).
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|Agricultural and Biological Sciences||43||4%|
|Computer and Information Science||24||2%|
|Student > Ph. D. Student||378||34%|
|Student > Master||182||16%|
|Student > Bachelor||72||6%|
|Professor > Associate Professor||51||5%|
"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