计算机科学 ›› 2017, Vol. 44 ›› Issue (Z11): 106-109.doi: 10.11896/j.issn.1002-137X.2017.11A.021
唐艳琴,潘志松,张艳艳
TANG Yan-qin, PAN Zhi-song and ZHANG Yan-yan
摘要： 在股票市场中,人们通常会依赖于股票的历史交易数据来进行推测。目前采用SVM方法进行预测的研究较多,但其模型复杂,耗时较长,而且通常只预测未来1天的数据。文中采用多输出的正则化方法来预测未来多天的走势,对多任务的学习方法进行改进,提出了一种基于多输出的学习方法。实验表明,与SVM支持向量机的方法相比,该方法在沪深300指数预测的均方差值上提高了约10倍,运行时长也减少了近3/4。
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