Coverart for item
The Resource Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining, Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii

Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining, Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii

Label
Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining
Title
Classification and modeling with linguistic information granules
Title remainder
advanced approaches advanced approaches to linguistic data mining
Statement of responsibility
Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii
Creator
Contributor
Subject
Genre
Language
eng
Summary
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod{u00AD} els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe{u00AD} matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com{u00AD} puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter{u00AD} net through words. We also communicate with others through words. 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 accuracy in classification and model{u00AD} ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability
Member of
Cataloging source
GW5XE
http://library.link/vocab/creatorName
Ishibuchi, Hisao
Dewey number
410
Illustrations
illustrations
Index
index present
LC call number
P203
LC item number
.I74 2005eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Nakashima, Tomoharu
  • Nii, Manabu
Series statement
Advanced information processing
http://library.link/vocab/subjectName
  • Language and languages
  • Linguistic analysis (Linguistics)
  • Linguistic informants
  • Linguistic models
  • Computational linguistics
  • Informatique
  • Computational linguistics
  • Language and languages
  • Linguistic analysis (Linguistics)
  • Linguistic informants
  • Linguistic models
Label
Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining, Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Control code
262677773
Dimensions
unknown
Extent
1 online resource (xi, 307 pages)
Form of item
online
Isbn
9783540207672
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
978-3-540-20767-2
Specific material designation
remote
System control number
(OCoLC)262677773
Label
Classification and modeling with linguistic information granules : advanced approaches advanced approaches to linguistic data mining, Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Control code
262677773
Dimensions
unknown
Extent
1 online resource (xi, 307 pages)
Form of item
online
Isbn
9783540207672
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
978-3-540-20767-2
Specific material designation
remote
System control number
(OCoLC)262677773

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