Note: You can access the solution to the Comprehension 1 questions from below:

In previous sessions, you learnt about the different ways of transforming woe transformation, the importance of information variables, and various other advantages and disadvantages of woe transformation.

You learnt how these methods can be used to treat **continuous variables**. In the next video. let’s explore it a little more.

This is how you can work on continuous variables.

In the next lecture, you will learn about some advanced transformation techniques such as spline transformation, interaction variables, mathematical transformation and principal component transformation. These transformations are hardly used in the model exercise. However, let’s see what the benefits and importance of these transformations are in the next lecture.

**Comprehension 2: Missing Value -WOE**

You saw that NA values can be treated with WOE values. However, you can replace the NA bucket with a bucket which shows similar woe values.

Let’s try to practice this with some examples. For this exercise, you are supposed to** download the data set** from below which is the subset data of the loan file:

In this file, there are two sheets. The first one contains the loan data set with only two variables — **Employment** **length** and **Default**. The second file contains the bucket distributions of employment length.

With this information, attempt the questions given below.