Features and Polynomial Regression

We can improve our features and the form of our hypothesis functions in a couple of different ways. We can combine multiple features into one. For example, we can combine x1​ and x2​ into a new feature x3​ by taking x1​⋅x2​.

Our hypothesis function need not be linear (a straight line) if that does not fit the data well.

We can change the behavior or curve of our hypothesis function by making it a quadratic, cubic or square root function (or any other form). Choose the one which best describes our function.

One important thing to keep in mind is, if you choose your features this way then feature scaling becomes very important.