The concept learning in the theory of rough sets

被引：0

作者：

Zhang, Qun-Feng ^{[1
]}

Jiang, Yu-Ting ^{[2
]}

Li, Zhi-Qiang ^{[3
]}

机构：

[1] Hebei Univ, Coll Math & Comp Sci, Key Lab Machine Learning & Computat Intelligence, Baoding 071002, Peoples R China

[2] Hebei Univ, Ind & Commercial Coll, Baoding 071002, Peoples R China

[3] Hebei Informat Engn Sch, Baoding 071000, Peoples R China

来源：

PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年

关键词：

rough set; concept learning; sample complexity; PAC-learnability;

D O I：

10.1109/ICMLC.2008.4620427

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Knowledge reduction in decision table is important in both theory and application, and it outputs a minimal algorithm as a result. Set of the samples fitting the minimal algorithm is a concept over the set of all possible instances. But in unfamiliar environment, decision table is obtained randomly. So the obtained concept is an approximation to a potential target concept. We discuss the model of this concept learning, sample complexity of its hypothesis space and PAC-learnability of its target concept class.

引用

页码：337 / +

页数：2

共 50 条

[31] Attribute classification based on the rough sets theory
Department of Computer Science, Guangdong Institution of Education, Guangzhou 510640, China
不详
Kong Zhi Li Lun Yu Ying Yong, 2008, 3 (591-595):
[32] Rough sets theory for multicriteria decision analysis
Greco, S
Matarazzo, B
Slowinski, R
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2001, 129 (01) : 1 - 47
[33] Rough sets and fuzzy sets theory applied to the sequential medical diagnosis
Zolnierek, Andrzej
Kurzynski, Marek
PATTERN RECOGNITION IN BIOINFORMATICS, PROCEEDINGS, 2007, 4774 : 311 - 322
[34] Incremental learning algorithm based on Rough sets
Li, C.S.
Yin, X.R.
Chen, S.F.
Xiaoxing Weixing Jisuanji Xitong/Mini-Micro Systems, 2001, 22 (08):
[35] Diagnose Learning Misconceptions Based on Rough Sets
Tsai, C. P.
Sheu, T. W.
Tzeng, J. W.
Chen, T. L.
Chiang, H. J.
Nagai, M.
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2014, 52 (02): : 63 - 75
[36] Deep learning architecture using rough sets and rough neural networks
Hassan, Yasser F.
KYBERNETES, 2017, 46 (04) : 693 - 705
[37] Formal Concept Analysis Based on Rough Set Theory and a Construction Algorithm of Rough Concept Lattice
Yang, Haifeng
EMERGING RESEARCH IN ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, 2011, 237 : 239 - 244
[38] The representation and resolution of rough sets based on the extended concept lattice
Hu, XG
Zhang, YH
Wang, XY
FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, PT 1, PROCEEDINGS, 2005, 3613 : 1309 - 1312
[39] Fast outlier detection using rough sets theory
Shaari, F.
Bakar, A. A.
Hamdan, A. R.
DATA MINING IX: DATA MINING, PROTECTION, DETECTION AND OTHER SECURITY TECHNOLOGIES, 2008, 40 : 25 - 34
[40] Incorporating the rough sets theory into travel demand analysis
Goh, C
Law, R
TOURISM MANAGEMENT, 2003, 24 (05) : 511 - 517

← 1 2 3 4 5 →