**4. When to apply PCA?**

PCA is widely applicable for unsupervised machine learning techniques, which helps to reduce the dimensions of the large data where the dataset does not contain the labelled column. The following are some of the situations where the PCA can be applied [4]:

Case 1: One wants to limit the number of variables but cannot figure out which ones to leave out entirely?

Case 2: One wants to make sure variables are unrelated to one another? Case 3: One thought, if the independent variables are less interpretable?
