02781oam 2200541I 450 991015318540332120240506102925.01-315-37069-71-4987-2413-21-315-35356-310.1201/9781315370699(CKB)3710000000960809(MiAaPQ)EBC4748356(MiAaPQ)EBC5209744(OCoLC)966398067(BIP)61806669(BIP)54933459(EXLCZ)99371000000096080920180331h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierLearning with uncertainty /Xizhao Wang, Junhai Zhai1st ed.Boca Raton :CRC Press,[2017]©20171 online resource (240 pages) illustrations, tables1-4987-2412-4 Includes bibliographical references and index.1. Uncertainty -- 2. Decision tree with uncertainty -- 3. Clustering under uncertainty environment -- 4. Active learning with uncertainty -- 5. Ensemble learning with uncertainty.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.Machine learningFuzzy decision makingDecision treesMachine learning.Fuzzy decision making.Decision trees.006.3/1Wang Xizhao865990Zhai JunhaiFlBoTFGFlBoTFGBOOK9910153185403321Learning with uncertainty1932677UNINA