I have some trouble to apply a multivariate linear regression on my data. I have two features gross_area which is continuous, nb_bathrooms which is discrete (1,2,3) and a dependent variable y which is the price. Firstly I have looked at the feature's distribution which is not normal (Skewed right). I removed some outliers. I standardized my features.I use OLS as cost function and "batch" gradient descent in order to find my parameters. I find my parameter I plot separately the gross_area against the price with parameter gross_area and the y-intercept, and a plot of the nb_bathrooms against the price with parameter nb_bathrooms and the y-intercept also.
This is what I got for the gross_area:
And for the nb_bedrooms:
So my questions are the following, How can I fit data like nb_bedrooms since I tried polynomial terms but does not seem to fit them better.