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https://ptsldigital.ukm.my/jspui/handle/123456789/579098| Title: | Modified kohonen network algorithm for selection of the initial centres of gustafson-kessel algorithm in credit scoring |
| Authors: | Sameer F Abu Bakar M. R (UPM) |
| Keywords: | Credit Scoring Decision-making Clustering Techniques Fuzzy Clustering Algorithms Gustafson-Kessel Algorithm Kohonen Network |
| Issue Date: | Jan-2017 |
| Description: | Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering results. The comparative was conducted using three credit scoring datasets: Australian, German and Taiwan. Internal and external indexes of validity clustering are computed and the proposed method was found to have the best performance in these three data sets. |
| News Source: | Pertanika Journals |
| ISSN: | 0128-7680 |
| Volume: | 25 |
| Pages: | 77-90 |
| Publisher: | Universiti Putra Malaysia Press |
| URI: | https://ptsldigital.ukm.my/jspui/handle/123456789/579098 |
| Appears in Collections: | Journal Content Pages/ Kandungan Halaman Jurnal |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_116452+Source01+Source010.PDF | 350.65 kB | Adobe PDF |  View/Open |
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