文件名称:PCA
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2016-04-05
- 文件大小：
- 1kb
- 下载次数：
- 0次
- 提 供 者：
- 木*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
PCA（Principal Component Analysis）不仅仅是对高维数据进行降维，更重要的是经过降维去除了噪声，发现了数据中的模式。
PCA把原先的n个特征用数目更少的m个特征取代，新特征是旧特征的线性组合，这些线性组合最大化样本方差，尽量使新的m个特征互不相关。从旧特征到新特征的映射捕获数据中的固有变异性。-PCA (Principal Component Analysis) is not just for high-dimensional data dimensionality reduction, more importantly, is the result of dimensionality reduction removes noise and found patterns in the data. PCA of the original n features with less number of m feature substitution, the new feature is a linear combination of the old features, which maximize a linear combination of the sample variance, try to make the new features of m uncorrelated. Mapping feature to capture data the old to the new features inherent variability.
PCA把原先的n个特征用数目更少的m个特征取代，新特征是旧特征的线性组合，这些线性组合最大化样本方差，尽量使新的m个特征互不相关。从旧特征到新特征的映射捕获数据中的固有变异性。-PCA (Principal Component Analysis) is not just for high-dimensional data dimensionality reduction, more importantly, is the result of dimensionality reduction removes noise and found patterns in the data. PCA of the original n features with less number of m feature substitution, the new feature is a linear combination of the old features, which maximize a linear combination of the sample variance, try to make the new features of m uncorrelated. Mapping feature to capture data the old to the new features inherent variability.
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下载文件列表
PCA\pca.m
PCA