Question

Hello, I got this attempt incorrect and I can't figure it out.

Do you know how to solve this correctly?

PCA Which of the following statements are true? Check l that apply Given an input r E Rn, PCA compresses it to a lower-dimensional vector zER PCA is susceptible to local optima; trying multiple random initializations may help. Even if all the input features are on very similar scales, we should still perform normalization(so that each feature has zero mean) before running PCA. PCA can be used only to reduce the dimensionality of the data by 1 (such as 3D to 2D, 2D to 1D)

Answer 1

Correct optios are ,

1 . Given an input x $\in\mathbb{R}^{n}$ , PCA compresses it to a lower -dimensional vector z $\in\mathbb{R}^{k}$

2. PCA is susceptible to local optima ; trying multiple random initializations may help .