Abstract
It is a key for the successes of data mining projects in practical situations to evaluate the obtained so many patterns as valuable knowledge effectively. In order to provide an effective support, we have been developing a rule evaluation support method based on the learning models of objective rule evaluation indices. In this paper, we report two improvements of this method and their evaluations. One is improved the learning algorithm selection in the proposed method by introducing a constructive meta-learning scheme. The other is improved the sorting efficiency of objective rule evaluation indices by combining them.
| Original language | English |
|---|---|
| Pages (from-to) | 180-197 |
| Number of pages | 18 |
| Journal | International Journal of Advanced Intelligence Paradigms |
| Volume | 2 |
| Issue number | 2-3 |
| DOIs | |
| Publication status | Published - 2010 |
Keywords
- Constructive meta-learning
- Data mining
- Objective rule evaluation index
- PCA
- Post-processing
- Principal component analysis
- Rule evaluation support
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
- Applied Mathematics