Python图像处理PCA算法完整源码

上传者: 42380711 | 上传时间: 2019-12-21 21:45:27 | 文件大小: 942KB | 文件类型: rar
数据降维   在实际生产生活中,我们所获得的数据集在特征上往往具有很高的维度,对高维度的数据进行处理时消耗的时间很大,并且过多的特征变量也会妨碍查找规律的建立。如何在最大程度上保留数据集的信息量的前提下进行数据维度的降低,是我们需要解决的问题。   对数据进行降维有以下优点:   (1)使得数据集更易使用   (2)降低很多算法的计算开销   (3)去除噪声   (4)使得结果易懂   降维技术作为数据预处理的一部分,即可使用在监督学习中也能够使用在非监督学习中。而降维技术主要有以下几种:主成分分析(Principal Component Analysis,PCA)、因子分析(Factor Analysis),以及独立成分分析(Independent Component Analysis, ICA)。其中主成分分析PCA应用最为广泛,本文也将详细介绍PCA。

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评论信息

  • Luo_Dongchen :
    骗子,代码根本跑不了
    2021-01-18
  • Luo_Dongchen :
    骗子,代码根本跑不了
    2021-01-18

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