1. PCA

Problem 1: Complete the following experiment. (20 Points)

Perform dimensionality reduction using PCA with n_components=2 for the iris dataset from sklearn (import datasets and call load_iris()).

Print the variance and explained variance ratio for those two components using pca.explained_variance and pca.explained_variance_ratio

Plot the dataset with reduced dimentions using a scatter plot.

Note: load_iris() returns a data structure with the data attribute being the features and the target attribute being the labels.