원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.6 No.3
2012.07
pp.81-88
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
We applied simulated annealing algorithm and decision tree to find set of single nucleotide polymorphisms relevant to a disease and build a risk prediction model. For time complexity problem of simulated annealing caused by initial set and candidate generation, we constructed an initial set of the variants by fast heuristic algorithm and proposed a transition rules based on contribution of available variants. The experiment results show that we can obtain new set of variants with the reduced number of variants and the improved prediction performance compared to others by traditional feature selection algorithms.
목차
Abstract
1. Introduction
2. Background
2.1 SNP
2.2 Simulates Annealing (SA)
3. Problem Definition
4. Related Works
5. Methods
5.1 Speedup Strategy
5.2 Transition Rule
5.3 Temperature Scheduling
6. Experiments and Results
6.1 Data
6.2 Evaluation Function
6.3 Experimental Results
7. Conclusion and Future Work
Acknow;dgements
References
1. Introduction
2. Background
2.1 SNP
2.2 Simulates Annealing (SA)
3. Problem Definition
4. Related Works
5. Methods
5.1 Speedup Strategy
5.2 Transition Rule
5.3 Temperature Scheduling
6. Experiments and Results
6.1 Data
6.2 Evaluation Function
6.3 Experimental Results
7. Conclusion and Future Work
Acknow;dgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보