计算机科学 ›› 2014, Vol. 41 ›› Issue (9): 239-242.doi: 10.11896/j.issn.1002-137X.2014.09.045
许烁娜,曾碧卿,熊芳敏
XU Shuo-na,ZENG Bi-qing and XIONG Fang-min
摘要： 在大数据环境下,当利用机器学习算法对训练样本进行分类时,训练数据的高维度严重制约了分类算法的性能。文中应用L1准则的稀疏性,提出了一种在线特征提取算法,并用该算法对训练实例进行分类。利用公开数据集对算法的性能进行了分析,结果表明,提出的在线特征提取算法能准确地对训练实例进行分类,因而能更好地适用于大数据环境下的数据挖掘。
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