Local and global characteristics-based kernel hybridization to increase optimal support vector machine performance for stock market prediction

标题
Local and global characteristics-based kernel hybridization to increase optimal support vector machine performance for stock market prediction
作者
关键词
Stock market movement prediction, Historical data series, Fruit fly optimization, Support vector machine, Radial basis function kernel, Polynomial kernel, Local, Global
出版物
KNOWLEDGE AND INFORMATION SYSTEMS
Volume -, Issue -, Pages -
出版商
Springer Nature America, Inc
发表日期
2018-08-31
DOI
10.1007/s10115-018-1263-1

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