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RBF커널 기반 주가 예측 벡터머신

Title
RBF커널 기반 주가 예측 벡터머신
Other Titles
Support Vector Machine for Predicting Stock Price Based on RBF Kernel
Author
Lee, Scott Uk-Jin
Issue Date
2017-06
Publisher
한국정보과학회
Citation
한국정보과학회 2017년 한국컴퓨터종합학술대회 논문집, Page. 856-858
Abstract
In current stock market,people are concerned more about the stock price prediction in recent years due to price fluctuation in the stock market and rapidly changing the prices. Therefore, in this paper we have proposed a price prediction solution by using Support Vector Machine(SVM) and Radial Basis Function(RBF) kernel to predict and the price of the stock from the previous values. To be exact, comparing with different parameters which are used in this model, we can get a set of optimum parameters to fit the regression and predict which is very close to the real value i.e. Price. We have applied our proposed approach on real time existing cases of stock market to ensure the correctness of results. Our experimental results show that percentage of the prediction success more than 70% which is very close to the previously existing values.
URI
http://www.dbpia.co.kr/Journal/ArticleDetail/NODE07207405http://repository.hanyang.ac.kr/handle/20.500.11754/103402
ISSN
2466-0825
Appears in Collections:
COLLEGE OF COMPUTING[E] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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