Predicting house prices with regression

Let's start with a simple problem, namely, predicting house prices in Boston. The problem is as follows: we are given several demographic and geographical attributes, such as the crime rate or the pupil-teacher ratio in the neighborhood. The goal is to predict the median value of a house in a particular area. As in the case of classification, we have some training data and want to build a model that can be generalized to other data.

This is one of the built-in datasets that scikit-learn comes with, so it is very easy to load the data into memory:

from sklearn.datasets import load_boston boston = load_boston() 

The boston object contains several attributes; in particular, contains the input ...

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