计算机科学 ›› 2015, Vol. 42 ›› Issue (Z6): 89-93.
潘舒,祁云嵩
PAN Shu and QI Yun-song
摘要: 现有的特征降维方法大致可分为特征提取和特征选择。在特征提取过程中,数据中的原始特征通过某些数据变换被映射到一个低维空间。提取出的特征尽管与原始特征相关,但不再具有原始特征的物理意义,即特征提取改变了原始数据的表达形式。与特征提取不同,特征选择则在原有的特征集中选择一个子集,选择出的特征子集中不再含有与数据分析任务相关性不大或冗余的那部分特征,其结果可能引起信息丢失。因而现有的数据降维方法几乎都不是保真降维,其降维后的数据仅适合特定的后续数据分析任务,因而只能算是特定数据分析任务的前期数据预处理。从多重假设检验方法的角度分析了高维数据保真降维的方法及研究的关键所在。
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