B$.1,2$ and $3$

C$.1,2$ and $4$

D$.$ All of the above

Solution: $($D$)$

Q$3.$ Which of the following the following clustering algorithms

suffers from the problem of convergence at local optima?

K$-$Means clustering algorithm.

Hierarchy clustering algorithm.

Expectation$-$Maximization clustering algorithm.

Gaussian Mixture Model clustering algorithm.

Options:

A$.1$ only

B$.2$ and $3$

C$.3$ and $4$

D$.1,3$ and $4$

Solution: $($D$)$

Q$4.$ How can Clustering $($Unsupervised Learning$)$ be used

improve the accuracy of the Linear Regression model

$($Supervised Learning$)?$

Creating an input feature for cluster ids as an ordinal variable.

Creating an input feature for cluster centroids as a continuous variab

Creating an input feature for cluster size as a continuous variable.