Reduce data dimension using PCA

2 次查看（过去 30 天）

Hg 2016-11-7

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/310974-reduce-data-dimension-using-pca

回答： Vassilis Papanastasiou 2021-12-17

pca() outputs the coefficient of the variables and principal components of a data. Is there any way to reduce the dimension of the data (340 observations), let say from 1200 dimension to 30 dimension using pca()?

2 个评论
显示无隐藏无

Adam 2016-11-7

You should just be able to keep the 30 largest components from running pca.

Hg 2016-11-8

在 MATLAB Online 中打开

I use

[residuals,reconstructed] = pcares(X,ndim)

请先登录，再进行评论。

请先登录，再回答此问题。

回答（1 个）

Vassilis Papanastasiou 2021-12-17

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/310974-reduce-data-dimension-using-pca#answer_857230

Hi Hg,

What you can do is to use pca directly. Say that X is of size 340x1200 (340 measurements and 1200 variables/dimensions). You want to get an output with reduced dimensionaty of 30. The code below will do that for you:

p = 30;

[~, pca_scores, ~, ~, var_explained] = pca(X, 'NumComponents', p);