The Composite Rule Induction System proposed by Liang (1992) that uses the tabular
approach and statistical inference to process qualitative and quantitative attributes separately
for generating better classification rules. Yang (2007) extended the method by incorporating
the second-order rules.
This Study further extends the previous method by including a mechanism for detecting
the existence of interaction effects. The detection method checks the degree of independence
between attributes to determine whether the second-order rules should be processed. In order
to evaluate the performance of the proposed method, an enhanced prototype system was
developed and both real and simulated data were used to compare its accuracy and rule
complexity with existing systems. The result shows that the enhanced system performs at
least as accurate as the existing system but is significantly better in the complexity of the
resulting knowledge base.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0825109-160011 |
| Date | 25 August 2009 |
| Creators | Qiu, Yun-han |
| Contributors | Wei-Bo Lee, Ting-Peng Liang, Deng-Neng Chen |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0825109-160011 |
| Rights | campus_withheld, Copyright information available at source archive |
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