Learning With Uncertainty

Informationen zum Autor Xizhao Wang, Junhai Zhai Zusammenfassung 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. Inhaltsverzeichnis Preface Symbols and Abbreviations Chapter 1 Uncertainty 13 Chapter 2 Decision Tree with Uncertainty Chapter 3 Clustering under Uncertainty Environment 77 Chapter 4 Active Learning with Uncertainty 121 Chapter 5 Ensemble learning with Uncertainty 173 Index

Product details

• Authors: Xizhao Wang, Xizhao (Hebei University Wang, Xizhao Zhai Wang, Wang Xizhao, Junhai Zhai, Junhai (Hebei University Zhai, Zhai Junhai
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 16.11.2016
• EAN: 9781498724128
• ISBN: 978-1-4987-2412-8
• No. of pages: 240
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; machine learning, MATHEMATICS / Probability & Statistics / General, Probability & statistics, Probability and statistics, COMPUTERS / Data Science / Machine Learning