Name
Title | ||
|---|---|---|
The Approach To Classifying Multi-Output Datasets Based On Cluster Validity Index Method |
Abstract | ||
|---|---|---|
A cluster validity index (CVI) classification method is applied to enhance the performance of existing Multiple-Attribute Decision Making (MADM) method. This paper proposed index-based method is called the FRM-index method which combined Fuzzy Set (FS), Rough Set (RS), and a cluster validity index function. The effectiveness of the proposed FRM-index method is evaluated by comparing the classification results obtained for the relating UCI datasets using a statistical approach. Overall, the results show that the proposed method not only provides a more reliable basis for the extraction of decision-making rules for multi-output datasets, but also fills out the uncertainty and facilitates an effective MADM built. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/icawst.2017.8256519 | 2017 IEEE 8TH INTERNATIONAL CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY (ICAST) |
Keywords | Field | DocType |
Multi-Attribute decision making, Fuzzy set theory, rough set theory, FRM-index method, cluster validity index | Data mining,Computer science,Cluster validity index,Rough set,Fuzzy set,Correlation | Conference |
ISSN | Citations | PageRank |
2325-5986 | 0 | 0.34 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kuang Yu Huang | 1 | 99 | 8.13 |
| Shann-Bin Chang | 2 | 0 | 0.34 |
| Lieh-Dai Yang | 3 | 0 | 0.34 |