Now that everything is in place, let’s build the model. You will follow a bottom-up approach for this, i.e., you will start by building the model with just one variable. Hence, the choice of this variable becomes very crucial. Let’s see which variable turns out to be ‘The Chosen One’.

Even though ‘**area**’ is the most correlated variable, it could explain only 28% of the variance. After that, we added **‘bathroom’ **as it had the second-highest correlation with the target variable. Then the model was able to explain 50% of the variance.

## Coming up

Adding two more variables has improved the model. From an adjusted R-squared value of 28%, it has moved to 50%. In the next segment, you will proceed with improving the model further.