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Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining

Author: Hisao Ishibuchi; Tomoharu Nakashima; Manabu Nii
Publisher: New York : Springer, ©2005.
Series: Advanced information processing.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:

While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of  Read more...

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Genre/Form: Electronic books
Classification
Additional Physical Format: Print version:
Ishibuchi, Hisao.
Classification and modeling with linguistic information granules.
New York : Springer, ©2005
(DLC) 2004114623
(OCoLC)59003662
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Hisao Ishibuchi; Tomoharu Nakashima; Manabu Nii
ISBN: 9783540268758 3540268758 3540207678 9783540207672 6610462518 9786610462513
OCLC Number: 262677773
Description: 1 online resource (xi, 307 pages) : illustrations.
Contents: Cover --
Table of Contents --
1. Linguistic Information Granules --
1.1 Mathematical Handling of Linguistic Terms --
1.2 Linguistic Discretization of Continuous Attributes --
2. Pattern Classification with Linguistic Rules --
2.1 Problem Description --
2.2 Linguistic Rule Extraction for Classification Problems --
2.3 Classification of New Patterns by Linguistic Rules --
2.4 Computer Simulations --
3. Learning of Linguistic Rules --
3.1 Reward-Punishment Learning --
3.2 Analytical Learning --
3.3 Related Issues --
4. Input Selection and Rule Selection --
4.1 Curse of Dimensionality --
4.2 Input Selection --
4.3 Genetic Algorithm-Based Rule Selection --
4.4 Some Extensions to Rule Selection --
5. Genetics-Based Machine Learning --
5.1 Two Approaches in Genetics-Based Machine Learning --
5.2 Michigan-Style Algorithm --
5.3 Pittsburgh-Style Algorithm --
5.4 Hybridization of the Two Approaches --
6. Multi-Objective Design of Linguistic Models --
6.1 Formulation of Three-Objective Problem --
6.2 Multi-Objective Genetic Algorithms --
6.3 Multi-Objective Rule Selection --
6.4 Multi-Objective Genetics-Based Machine Learning --
7. Comparison of Linguistic Discretization with Interval Discretization --
7.1 Effects of Linguistic Discretization --
7.2 Specification of Linguistic Discretization from Interval Discretization --
7.3 Comparison Using Homogeneous Discretization --
7.4 Comparison Using Inhomogeneous Discretization --
8. Modeling with Linguistic Rules --
8.1 Problem Description --
8.2 Linguistic Rule Extraction for Modeling Problems --
8.3 Modeling of Nonlinear Fuzzy Functions --
9. Design of Compact Linguistic Models --
9.1 Single-Objective and Multi-Objective Formulations --
9.2 Multi-Objective Rule Selection --
9.3 Fuzzy Genetics-Based Machine Learning --
9.4 Comparison of Two Schemes --
10. Linguistic Rules with Consequent Real Numbers --
10.1 Consequent Real Numbers --
10.2 Local Learning of Consequent Real Numbers --
10.3 Global Learning --
10.4 Effect of the Use of Consequent Real Numbers --
10.5 Twin-Table Approach --
11. Handling of Linguistic Rules in Neural Networks --
11.1 Problem Formulation --
11.2 Handling of Linguistic Rules Using Membership Values --
11.3 Handling of Linguistic Rules Using Level Sets --
11.4 Handling of Linguistic Rules Using Fuzzy Arithmetic --
12. Learning of Neural Networks from Linguistic Rules --
12.1 Back-Propagation Algorithm --
12.2 Learning from Linguistic Rules for Classification Problems --
12.3 Learning from Linguistic Rules for Modeling Problems --
13. Linguistic Rule Extraction from Neural Networks --
13.1 Neural Networks and Linguistic Rules --
13.2 Linguistic Rule Extraction for Modeling Problems --
13.3 Linguistic Rule Extraction for Classification Problems --
13.4 Difficulties and Extensions --
14. Modeling of Fuzzy Input-Output Relations --
14.1 Modeling of Fuzzy Number-Valued Functions --
14.2 Modeling of Fuzzy Mappings --
14.3 Fuzzy Classification
Series Title: Advanced information processing.
Responsibility: Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii.
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