원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.7 No.6
2014.12
pp.151-162
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Now a large scale of data every day, the large-scale data is usually in the form of database storage. The law of the people wants to find useful or knowledge, thus was born the Data Mining technology. SVM (Support Vector Machine, SVM) is a very useful method in data mining, this paper mainly discusses the Support Vector Machine (SVM) play a key role in nuclear techniques and the selection of model parameters is analyzed and evaluated. This article some methods about how to construct the kernel function is introduced for the model to find suitable kernel function is to provide some reference strategies and proposed kernel function method for the simulation analysis.
목차
Abstract
1. Introduction
2. Related Works
3. Proposed Scheme
3.1 Commonly Used Kernel Function is Introduced
3.2 The Structure of the Kernel Function
3.3 The Selection of Model Parameters
4. The Experimental Results and Analysis
4.1 Experimental Platform and Data
4.2 The Experiment Results Analysis
5. Conclusion
References
1. Introduction
2. Related Works
3. Proposed Scheme
3.1 Commonly Used Kernel Function is Introduced
3.2 The Structure of the Kernel Function
3.3 The Selection of Model Parameters
4. The Experimental Results and Analysis
4.1 Experimental Platform and Data
4.2 The Experiment Results Analysis
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보