Learning with uncertainty
by Wang, Xizhao
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: Decision tree learning with uncertainty; clustering under uncertainty environment; active learning based on uncertainty criterion; and ensemble learning in a framework of uncertainty.
Read More ↓Title Statements
- Full title :Learning with uncertainty / Xizhao Wang, Junhai Zhai.
Summary
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: Decision tree learning with uncertainty; clustering under uncertainty environment; active learning based on uncertainty criterion; and ensemble learning in a framework of uncertainty.
Read More ↓Edition Statements
- Publication Date:2016
Publication Statements
- Publisher(s):CRC Press
- Place of Publication:Boca Raton
- Language:eng
- Publication Date:2016
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9781498724135, 1498724132, 9781315353562, 1315353563
- DOI:10.1201/9781315370699
- oclc:ocn992912933
- LC Classification:Q325.5
- Dewey Decimal:006.3/1
Table of Contents
Cover; Half Title; Title Page; Copyright Page; Table of Contents; Contents; Preface; Symbols and Abbreviations; 1: Uncertainty; 1.1 Randomness; 1.1.1 Entropy; 1.1.2 Joint Entropy and Conditional Entropy; 1.1.3 Mutual Information; 1.2 Fuzziness; 1.2.1 Definition and Representation of Fuzzy Sets; 1.2.2 Basic Operations and Properties of Fuzzy Sets; 1.2.3 Fuzzy Measures; 1.3 Roughness; 1.4 Nonspecificity; 1.5 Relationships among the Uncertainties; 1.5.1 Entropy and Fuzziness; 1.5.2 Fuzziness and Ambiguity; References; 2: Decision Tree with Uncertainty; 2.1 Crisp Decision Tree.
2.1.1 ID3 Algorithm2.1.2 Continuous-Valued Attributes Decision Trees; 2.2 Fuzzy Decision Tree; 2.3 Fuzzy Decision Tree Based on Fuzzy Rough Set Techniques; 2.3.1 Fuzzy Rough Sets; 2.3.2 Generating Fuzzy Decision Tree with Fuzzy Rough Set Technique; 2.4 Improving Generalization of Fuzzy Decision Tree by Maximizing Fuzzy Entropy; 2.4.1 Basic Idea of Refinement; 2.4.2 Globally Weighted Fuzzy If-Then Rule Reasoning; 2.4.3 Refinement Approach to Updating the Parameters; 2.4.3.1 Maximum Fuzzy Entropy Principle; References; 3: Clustering under Uncertainty Environment; 3.1 Introduction.
3.2 Clustering Algorithms Base…
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