MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03514nam a22004935i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
978-3-540-26875-8 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20170628034308.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
100301s2005 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783540268758 |
| -- |
978-3-540-26875-8 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/b138232 |
| Source of number or code |
doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q334-342 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
TJ210.2-211.495 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
TJFM1 |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
COM004000 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ishibuchi, Hisao. |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Classification and Modeling with Linguistic Information Granules |
| Medium |
[electronic resource] : |
| Remainder of title |
Advanced Approaches to Linguistic Data Mining / |
| Statement of responsibility, etc |
by Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii. |
| 264 #1 - |
|---|
| -- |
Berlin, Heidelberg : |
| -- |
Springer Berlin Heidelberg, |
| -- |
2005. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XII, 308 p. |
| Other physical details |
online resource. |
| 336 ## - |
|---|
| -- |
text |
| -- |
txt |
| -- |
rdacontent |
| 337 ## - |
|---|
| -- |
computer |
| -- |
c |
| -- |
rdamedia |
| 338 ## - |
|---|
| -- |
online resource |
| -- |
cr |
| -- |
rdacarrier |
| 347 ## - |
|---|
| -- |
text file |
| -- |
PDF |
| -- |
rda |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Advanced Information Processing |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Linguistic Information Granules -- Pattern Classification with Linguistic Rules -- Learning of Linguistic Rules -- Input Selection and Rule Selection -- Genetics-Based Machine Learning -- Multi-Objective Design of Linguistic Models -- Comparison of Linguistic Discretization with Interval Discretization -- Modeling with Linguistic Rules -- Design of Compact Linguistic Models -- Linguistic Rules with Consequent Real Numbers -- Handling of Linguistic Rules in Neural Networks -- Learning of Neural Networks from Linguistic Rules -- Linguistic Rule Extraction from Neural Networks -- Modeling of Fuzzy Input—Output Relations. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod 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 matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com 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 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 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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Models and Principles. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nakashima, Tomoharu. |
| Relator term |
author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nii, Manabu. |
| Relator term |
author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9783540207672 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Advanced Information Processing |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/b138232">http://dx.doi.org/10.1007/b138232</a> |
| 912 ## - |
|---|
| -- |
ZDB-2-SCS |
