Earticle

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

키워드

저자

• Wang Chunhong [ Computer Department, Inner Mongolia University of Finance and Economics, Hohhot, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605