Question

Which of the following statements is true about PCA?
(i) We must standardize the data before applying PCA.
(ii) We should select the principal components which explain the highest variance
(iii) We should select the principal components which explain the lowest variance
(iv) We can use PCA for visualizing the data in lower dimensions
A. (i), (ii) and (iv)
B. (ii) and (iv)
C. (iii) and (iv)
D. (i) and (iii)

Answer 1

A. (i), (ii) and (iv)

Answer 2

A. (i), (ii), and (iv)  statements are true about PCA.

About PCA :

(i) We must standardize the data before applying PCA.

(ii) We should select the principal components which explain the highest variance

(iv) We can use PCA for visualizing the data in lower dimensions

• Through linear combinations, Principal Component Analysis (PCA) is used to explain the variance-covariance structure of a set of variables. It's a popular approach for reducing dimensionality.

• It's important to note that PCA is an unsupervised method, which means it doesn't employ labels in its calculations.