Question

1. What are two benefits of using Principal Components Analysis (PCA)?

Answer 1

We have many datasets which are high dimensional and we cannot direct visualize the data as we have only three dimensions.So,to analyze the data without losing much information we need the principal component analysis that is PCA

The main benefits of PCA are:-

-PCA reduces the dimensionality of data by performing different variations on datasets so that we can see the information which is important.To reduce the dimensionality PCA creates the new variables which are artificial are called principal components that is PC.These are the combination of variables in the datasets.

-PCA provides the data visualization

Suppose we have large number of variables of a particular entity,we cannot plot this data in a different directions as we can only plot the data in a three key dimensions.So,PCA tranforms the higher dimensional space to lower dimensional space as we can plot this data in a three dimensions and gives the direct visualization of data.