MOGA for Multi-Level Fuzzy Data Mining

被引：0

作者：

Chen, Chun-Hao ^{[1
]}

Ho, Chi-Hsuan ^{[1
]}

Hong, Tzung-Pei ^{[2
]}

Lin, Wei-Tee ^{[3
]}

机构：

[1] Tamkang Univ, Dept Comp Sci & Infonnat Engn, Taipei, Taiwan

[2] Natl Univ Kaohsiung, Dept Comp Sci & Informat Engn, Kaohsiung, Taiwan

[3] Natl Cheng Kung Univ, Dept Comp Sci & Informat Engn, Tainan, Taiwan

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC 2012) | 2012年

关键词：

data mining; multi-objective genetic algorithm; multi-concept levels; membership function; fuzzy association rule; LEVEL ASSOCIATION RULES; MEMBERSHIP FUNCTIONS; GENETIC ALGORITHMS;

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：

In this paper, we propose a Multi-Objective Multi-Level Genetic-Fuzzy Mining (MOMLGFM) algorithm for mining a set of non-dominated membership functions for mining multi-level fuzzy association rules. It first encodes the membership functions of each item class (category) into a chromosome according to the given taxonomy. The two objective functions of each chromosome are then calculated. The first one is the summation of large 1-itemsets of each item in different concept levels, and the second one is the suitability of membership functions. The fitness value of each individual is then evaluated by these two objective functions. After the GA process terminates, various sets of membership functions could be used for deriving multiple-level fuzzy association rules according to decision maker. Experimental results on a simulation dataset also show the effectiveness of the algorithm.

引用

页码：32 / 37

页数：6

共 50 条

[31] An Ontology for Multi-Level Data Fusion
Steinberg, Alan N.
[J]. 2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022), 2022,
[32] Mining Rare Itemsets on Multi-Level Hierarchies Database
Ouypornkochagorn, Taweechai
[J]. INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, IMECS 2012, VOL I, 2012, : 487 - 491
[33] Multi-Level Mining and Visualization of Informative Association Rules
Usman, Muhammad
Usman, M.
[J]. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2016, 32 (04) : 1061 - 1078
[34] Multi-level mining and visualization of informative association rules
[J]. 1600, Institute of Information Science (32):
[35] Developing an efficient knowledge discovering model for mining fuzzy multi-level sequential patterns in sequence databases
Huang, Tony Cheng-Kui
[J]. FUZZY SETS AND SYSTEMS, 2009, 160 (23) : 3359 - 3381
[36] Developing an Efficient Knowledge Discovering Model for Mining Fuzzy Multi-level Sequential Patterns in Sequence Databases
Huang, Tony Cheng-kui
[J]. 2009 INTERNATIONAL CONFERENCE ON NEW TRENDS IN INFORMATION AND SERVICE SCIENCE (NISS 2009), VOLS 1 AND 2, 2009, : 362 - 371
[37] An Algorithm of Multi-Level Fuzzy Association Rules Mining With Multiple Minimum Supports in Network Faults Diagnosis
Liu, Pan
Li, Xing-ming
Feng, Yan-qing
[J]. 2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 884 - 888
[38] Interactive fuzzy programming for multi-level linear programs with fuzzy numbers
Sakawa, M
Nishizaki, I
Uemura, Y
[J]. 1998 SECOND INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ELECTRONIC SYSTEMS, KES'98 PROCEEDINGS, VOL 1, 1998, : 109 - 118
[39] The Multi-level Fuzzy Comprehensive Evaluation of Enterprise Growth
Xue Bing
[J]. CALL OF PAPER PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING, 2008, : 1283 - 1287
[40] Multi-level mapping and its application in fuzzy sensors
Han, JF
Luo, WG
Hong, WX
[J]. ISTM/99: 3RD INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, 1999, : 215 - 218

← 1 2 3 4 5 →