Variable Selection for Artificial Neural Networks with Applications for Stock Price Prediction

被引：12

作者：

Kim, Gang-Hoo ^{[1
]}

Kim, Sung-Ho ^{[1
]}

机构：

[1] Korea Adv Inst Sci & Technol, Dept Math Sci, Daejeon 34141, South Korea

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2019年 / 33卷 / 01期

关键词：

D O I：

10.1080/08839514.2018.1525850

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a new Artificial neural network (ANN) method where we select a set of variables as input variables to the ANN. The selection is made so that the input variables may be informative for a target variable as much as possible. The proposed method compared favorably with the existing ANN methods when their performances were evaluated based on 488 stocks in S&P500 in terms of prediction accuracy.

引用

页码：54 / 67

页数：14

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