计算机科学 ›› 2014, Vol. 41 ›› Issue (12): 226-230.doi: 10.11896/j.issn.1002-137X.2014.12.049
陆慧娟,魏莎莎,关伟,缪燕子
LU Hui-juan,WEI Sha-sha,GUAN Wei and MIAO Yan-zi
摘要: 提出一种基于鱼群优化算法和Cholesky分解的改进的正则极限学习机算法(FSC-RELM)来对基因表达数据进行分类。FSC-RELM算法中,首先用鱼群优化算法对RELM输入层权值进行优化,其中目标函数定义为误差函数的倒数;再对RELM输出层权值矩阵进行分解,采用Cholesky分解法进行优化,以提高算法速度,减少训练时间。为了评价算法性能,对若干标准基因数据集进行了实验,结果表明,FSC-RELM算法在较短的时间内可以获得较高的分类精度,性能优异。
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