Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

15.5 Case Study: Multiple Linear Regression with the California Housing Dataset

In Chapter 10’s Intro to Data Science section, we performed simple linear regression on a small weather data time series using pandas, Seaborn’s regplot function and the SciPy’s stats module’s linregress function. In the previous section, we reimplemented that same example using scikit-learn’s LinearRegression estimator, Seaborn’s scatterplot function and Matplotlib’s plot function. Now, we’ll perform linear regression with a much larger real-world dataset.

The California Housing dataset⁷ bundled with scikit-learn has 20,640 samples, each with eight numerical features. We’ll perform a multiple linear regression that uses all eight numerical features to make more ...