Abstract
In this paper, we present an evaluation of learning algorithms of 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 processes in a data mining process. However, it is difficult for human experts to completely evaluate several thousands of rules from a large dataset with noises. To reduce the costs in such rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which learn from objective indices for mined classification rules and evaluations by a human expert for each rule. To enhance adaptability of rule evaluation models, we introduced a constructive meta-learning system to choose proper learning algorithms. Then, we have done the case study on the meningitis data mining as an actual problem.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Conference on Data Mining, ICDM |
| Pages | 305-310 |
| Number of pages | 6 |
| Publication status | Published - 2006 |
| Event | 6th IEEE International Conference on Data Mining - Workshops, ICDM 2006 - Hong Kong, China Duration: 2006 Dec 18 → 2006 Dec 18 |
Other
| Other | 6th IEEE International Conference on Data Mining - Workshops, ICDM 2006 |
|---|---|
| Country | China |
| City | Hong Kong |
| Period | 06/12/18 → 06/12/18 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Evaluating learning algorithms composed by a constructive meta-learning scheme for a rule evaluation support method. / Abe, Hidenao; Tsumoto, Shusaku; Ohsaki, Miho; Yamaguchi, Takahira.
Proceedings - IEEE International Conference on Data Mining, ICDM. 2006. p. 305-310 4063644.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Evaluating learning algorithms composed by a constructive meta-learning scheme for a rule evaluation support method
AU - Abe, Hidenao
AU - Tsumoto, Shusaku
AU - Ohsaki, Miho
AU - Yamaguchi, Takahira
PY - 2006
Y1 - 2006
N2 - In this paper, we present an evaluation of learning algorithms of 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 processes in a data mining process. However, it is difficult for human experts to completely evaluate several thousands of rules from a large dataset with noises. To reduce the costs in such rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which learn from objective indices for mined classification rules and evaluations by a human expert for each rule. To enhance adaptability of rule evaluation models, we introduced a constructive meta-learning system to choose proper learning algorithms. Then, we have done the case study on the meningitis data mining as an actual problem.
AB - In this paper, we present an evaluation of learning algorithms of 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 processes in a data mining process. However, it is difficult for human experts to completely evaluate several thousands of rules from a large dataset with noises. To reduce the costs in such rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which learn from objective indices for mined classification rules and evaluations by a human expert for each rule. To enhance adaptability of rule evaluation models, we introduced a constructive meta-learning system to choose proper learning algorithms. Then, we have done the case study on the meningitis data mining as an actual problem.
UR - http://www.scopus.com/inward/record.url?scp=78449301983&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78449301983&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78449301983
SN - 0769527027
SN - 9780769527024
SP - 305
EP - 310
BT - Proceedings - IEEE International Conference on Data Mining, ICDM
ER -