TY - GEN
T1 - Evaluating learning algorithms to construct rule evaluation models based on objective rule evaluation indices
AU - Abe, Hidenao
AU - Tsumoto, Shusaku
AU - Ohsaki, Miho
AU - Yamaguchi, Takahira
PY - 2007
Y1 - 2007
N2 - In the present paper, we describe an evaluation of our rule evaluation support method with constructive meta-learning scheme 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 the data mining process. However, it is difficult for human experts to completely evaluate several thousand of rules from a large dataset with noises. To reduce the costs in such a rule evaluation task, we have developed a 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 the adaptability of rule evaluation models, we introduced a constructive meta-learning scheme to choose proper learning algorithms. Then, we performed the case study on the meningitis data mining as an actual problem. In addition, we evaluated the proposed method using the ten rule sets obtained from the ten UCI datasets. The obtained results demonstrate the applicability of the proposed rule evaluation support method.
AB - In the present paper, we describe an evaluation of our rule evaluation support method with constructive meta-learning scheme 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 the data mining process. However, it is difficult for human experts to completely evaluate several thousand of rules from a large dataset with noises. To reduce the costs in such a rule evaluation task, we have developed a 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 the adaptability of rule evaluation models, we introduced a constructive meta-learning scheme to choose proper learning algorithms. Then, we performed the case study on the meningitis data mining as an actual problem. In addition, we evaluated the proposed method using the ten rule sets obtained from the ten UCI datasets. The obtained results demonstrate the applicability of the proposed rule evaluation support method.
KW - Dato mining
KW - Post-processing
KW - Rule evaluation support
KW - rule evaluation index
UR - http://www.scopus.com/inward/record.url?scp=48049085868&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48049085868&partnerID=8YFLogxK
U2 - 10.1109/COGINF.2007.4341893
DO - 10.1109/COGINF.2007.4341893
M3 - Conference contribution
AN - SCOPUS:48049085868
SN - 1424413273
SN - 9781424413270
T3 - Proceedings of the 6th IEEE International Conference on Cognitive Informatics, ICCI 2007
SP - 212
EP - 221
BT - Proceedings of the 6th IEEE International Conference on Cognitive Informatics, ICCI 2007
T2 - 6th IEEE International Conference on Cognitive Informatics, ICCI 2007
Y2 - 6 August 2007 through 8 August 2007
ER -