Learning a Table from a Table with Non-deterministic Information: A Perspective

被引：0

作者：

Wu, Mao ^{[1
]}

Yamaguchi, Naoto ^{[1
]}

Nakata, Michinori ^{[2
]}

Sakai, Hiroshi ^{[1
]}

机构：

[1] Kyushu Inst Technol, Fac Engn, Kitakyushu, Fukuoka 804, Japan

[2] Josai Int Univ, Fac Management & Informat Sci, Chiba 283, Japan

来源：

ADVANCED MACHINE LEARNING TECHNOLOGIES AND APPLICATIONS | 2012年 / 322卷

基金：

日本学术振兴会;

关键词：

Estimation of actual information; Constraint; Rough sets; Data dependency; Rules; GENERATION; RULES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rough Non-deterministic Information Analysis (RNIA) is a rough sets-based framework for handling tables with exact and inexact data. In this framework, we have mainly investigated rough sets-based concepts in a table with non-deterministic information and some algorithms. This paper considers perspective on a new issue that how we estimate a table with actual information from a table with non-deterministic information by adding some constraint. This issue in RNIA slightly seems analogous to backpropagation in Neural Networks.

引用

页码：24 / +

页数：2

共 17 条

[1] Aldrich J, 1997, STAT SCI, V12, P162
[2] [Anonymous], 1994, The Roots of Backpropagation
[3] Cook W. J., 1997, COMBINATORIAL OPTIMI
[4] Grzymala-Busse JW, 2004, LECT NOTES COMPUT SC, V3100, P78
[5] Rules in incomplete information systems
Kryszkiewicz, M
[J]. INFORMATION SCIENCES, 1999, 113 (3-4) : 271 - 292
[6] REPRESENTATION OF NONDETERMINISTIC INFORMATION
ORLOWSKA, E
PAWLAK, Z
[J]. THEORETICAL COMPUTER SCIENCE, 1984, 29 (1-2) : 27 - 39
[7] Pawlak Z, 1983, SYSTEMY INFORM PODST
[8] Pawlak Z., 1991, Theoretical Aspects of Reasoning About Data, Rough sets, DOI [10.1007/978-94-011-3534-4, DOI 10.1007/978-94-011-3534-4]
[9] Peters G., 2012, SELECTED METHODS APP
[10] Polkowski L., 1998, ROUGH SETS KNOWLED 1

← 1 2 →