Exceptional Association Rule Set Discovery from Community-dwelling Elderly People Database

Kaoru Shimada, Hisae Aoki, Keiko Kubota, Satoru Haresaku, Shinsuke Mizutani, Toru Naito, Michio Ueno

Research output: Contribution to journalArticle

Abstract

An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.
Original languageEnglish
Pages (from-to)3285-3290
Number of pages6
Journal 2018 IEEE International Conference on Systems, Man, and Cybernetics
Publication statusPublished - 2018

Fingerprint

Association rules
Health care
Medicine

Cite this

Exceptional Association Rule Set Discovery from Community-dwelling Elderly People Database. / Shimada, Kaoru; Aoki, Hisae; Kubota, Keiko; Haresaku, Satoru; Mizutani, Shinsuke; Naito, Toru; Ueno, Michio.

In: 2018 IEEE International Conference on Systems, Man, and Cybernetics, 2018, p. 3285-3290.

Research output: Contribution to journalArticle

Shimada, Kaoru ; Aoki, Hisae ; Kubota, Keiko ; Haresaku, Satoru ; Mizutani, Shinsuke ; Naito, Toru ; Ueno, Michio. / Exceptional Association Rule Set Discovery from Community-dwelling Elderly People Database. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics. 2018 ; pp. 3285-3290.
@article{e70f4780a01e4f09aa3ca0b2725c3d03,
title = "Exceptional Association Rule Set Discovery from Community-dwelling Elderly People Database",
abstract = "An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.",
author = "Kaoru Shimada and Hisae Aoki and Keiko Kubota and Satoru Haresaku and Shinsuke Mizutani and Toru Naito and Michio Ueno",
year = "2018",
language = "English",
pages = "3285--3290",
journal = "2018 IEEE International Conference on Systems, Man, and Cybernetics",
publisher = "IEEE",

}

TY - JOUR

T1 - Exceptional Association Rule Set Discovery from Community-dwelling Elderly People Database

AU - Shimada, Kaoru

AU - Aoki, Hisae

AU - Kubota, Keiko

AU - Haresaku, Satoru

AU - Mizutani, Shinsuke

AU - Naito, Toru

AU - Ueno, Michio

PY - 2018

Y1 - 2018

N2 - An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.

AB - An extended method to discover exceptional association rule sets from incomplete databases is proposed. In an exceptional rule set, each itemset X, Y has a weak or no statistical relation to class C; however, the join of X and Y has a strong relation to C. An exceptional rule set can be used to infer long rules for the join of X and Y and to discover rare rules. The proposed method calculates the rule evaluation odds ratio directly. In this study, the method is applied to rule discovery using a database of community-dwelling elderly. Experimental results demonstrate that the proposed method can help discover interesting rare rules and exceptional association rule sets. The results show the effectiveness of the proposed method in the fields of medicine and health care.

M3 - Article

SP - 3285

EP - 3290

JO - 2018 IEEE International Conference on Systems, Man, and Cybernetics

JF - 2018 IEEE International Conference on Systems, Man, and Cybernetics

ER -