LEADER 02781oam 2200541I 450 001 9910153185403321 005 20240506102925.0 010 $a1-315-37069-7 010 $a1-4987-2413-2 010 $a1-315-35356-3 024 7 $a10.1201/9781315370699 035 $a(CKB)3710000000960809 035 $a(MiAaPQ)EBC4748356 035 $a(MiAaPQ)EBC5209744 035 $a(OCoLC)966398067 035 $a(BIP)61806669 035 $a(BIP)54933459 035 $a(EXLCZ)993710000000960809 100 $a20180331h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aLearning with uncertainty /$fXizhao Wang, Junhai Zhai 205 $a1st ed. 210 1$aBoca Raton :$cCRC Press,$d[2017] 210 4$dİ2017 215 $a1 online resource (240 pages) $cillustrations, tables 311 08$a1-4987-2412-4 320 $aIncludes bibliographical references and index. 327 $a1. Uncertainty -- 2. Decision tree with uncertainty -- 3. Clustering under uncertainty environment -- 4. Active learning with uncertainty -- 5. Ensemble learning with uncertainty. 330 $aLearning 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. 606 $aMachine learning 606 $aFuzzy decision making 606 $aDecision trees 615 0$aMachine learning. 615 0$aFuzzy decision making. 615 0$aDecision trees. 676 $a006.3/1 700 $aWang$b Xizhao$0865990 702 $aZhai$b Junhai 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910153185403321 996 $aLearning with uncertainty$91932677 997 $aUNINA