Abstract
In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective indices of mined classification rules and evaluations of a human expert for each rule. To evaluate performances of learning algorithms for constructing rule evaluation models, we have done a case study on the meningitis data mining as an actual problem. In addition, we have also evaluated our method on four rulesets from the four UCI datasets. Then we show the availability of our rule evaluation support method.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 93-104 |
| Number of pages | 12 |
| Volume | 3885 LNAI |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 3rd International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006 - Tarragona, Spain Duration: 2006 Apr 3 → 2006 Apr 5 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3885 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 3rd International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006 |
|---|---|
| Country | Spain |
| City | Tarragona |
| Period | 06/4/3 → 06/4/5 |
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ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
Cite this
Evaluating model construction methods with objective rule evaluation indices to support human experts. / Abe, Hidenao; Tsumoto, Shusaku; Ohsaki, Miho; Yamaguchi, Takahira.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3885 LNAI 2006. p. 93-104 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3885 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Evaluating model construction methods with objective rule evaluation indices to support human experts
AU - Abe, Hidenao
AU - Tsumoto, Shusaku
AU - Ohsaki, Miho
AU - Yamaguchi, Takahira
PY - 2006
Y1 - 2006
N2 - In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective indices of mined classification rules and evaluations of a human expert for each rule. To evaluate performances of learning algorithms for constructing rule evaluation models, we have done a case study on the meningitis data mining as an actual problem. In addition, we have also evaluated our method on four rulesets from the four UCI datasets. Then we show the availability of our rule evaluation support method.
AB - In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective indices of mined classification rules and evaluations of a human expert for each rule. To evaluate performances of learning algorithms for constructing rule evaluation models, we have done a case study on the meningitis data mining as an actual problem. In addition, we have also evaluated our method on four rulesets from the four UCI datasets. Then we show the availability of our rule evaluation support method.
UR - http://www.scopus.com/inward/record.url?scp=33745593689&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745593689&partnerID=8YFLogxK
U2 - 10.1007/11681960_11
DO - 10.1007/11681960_11
M3 - Conference contribution
SN - 3540327800
SN - 9783540327806
VL - 3885 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 93
EP - 104
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -