Four years have passed since the first edition of this book. During this time I have had the opportunity to apply it in classes obtaining feedback from students and inspiration for improvements. I have also benefited from many comments by users of the book. For the present second edition large parts of the book have undergone major revision, although the basic concept - concise but sufficiently rigorous mathematical treatment with emphasis on computer applications to real datasets -, has been retained. The second edition improvements are as follows: - Inclusion of R as an application tool. As...
Four years have passed since the first edition of this book. During this time I have had the opportunity to apply it in classes obtaining feedback fro...
This is a unique book on how probability affects our everyday lives. It guides the reader in an almost chronological trip through the fascinating and amazing laws of chance, omnipresent in the natural world and in our daily lives. Along the way many fascinating topics are discussed. These include challenging probability paradoxes, "paranormal" coincidences, game odds, and causes and effects. Finally the author discusses possibilities and limitations of learning the laws of a Universe immersed in chance events. This charming book, with its many easy-to-follow mathematical examples, will...
This is a unique book on how probability affects our everyday lives. It guides the reader in an almost chronological trip through the fascinating a...
Joaquim P. Marque Luis M. a. Silva Jorge M. F. Santos
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals.
Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE like concept...
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of th...
