Bayesian Classification

In this part you have two datasets. Each dataset contains two classes and each class generated from one Gaussian distribution. In this part you have to construct two Bayesian classifiers so as to classify both train and test data.

Plot the decision boundary and classification results:

Plot estimated PDFs (3D):

Plot estimated PDFs along with the decision boundary (2D):

Comparison of two datasets:

Due to the greater variance of the first dataset, the horizontal stretching of curves of the first dataset is less than that of the second dataset.