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Productivity Press
16 November 2016
Probability & statistics; Machine learning
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion, and (4) Ensemble learning in a framework of uncertainty. The book starts with the introduction to uncertainty including randomness, roughness, fuzziness and non-specificity and then comprehensively discusses a number of key issues in learning with uncertainty, such as uncertainty representation in learning, the influence of uncertainty on the performance of learning system, the heuristic design with uncertainty, etc.

Most contents of the book are our research results in recent decades. The purpose of this book is to help the readers to understand the impact of uncertainty on learning processes. It comes with many examples to facilitate understanding. The book can be used as reference book or textbook for researcher fellows, senior undergraduates and postgraduates majored in computer science and technology, applied mathematics, automation, electrical engineering, etc.
By:   Xizhao Wang (Hebei University Baoding PR of China), Junhai Zhai (Hebei University, Baoding, PR of China)
Imprint:   Productivity Press
Country of Publication:   United States
Dimensions:   Height: 235mm,  Width: 156mm, 
Weight:   476g
ISBN:   9781498724128
ISBN 10:   1498724124
Pages:   227
Publication Date:   16 November 2016
Audience:   College/higher education ,  College/higher education ,  Primary ,  Primary
Format:   Hardback
Publisher's Status:   Active

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