Making Decisions with Linear Equations

The method of least squares regression analysis dates back to the time of Carl Friedrich Gauss in the 18^th century. For over two centuries, many algorithms have been built on top of it or have been inspired by it in some form. These linear models are possibly the most commonly used algorithms today for both regression and classification. We will start this chapter by looking at the basic least squares algorithm, then we will move on to more advanced algorithms as the chapter progresses.

Here is a list of the topics covered in this chapter:

• Understanding linear models
• Predicting house prices in Boston
• Regularizing the regressor
• Finding regression intervals
• Additional linear regressors
• Using logistic regression for classification
• Additional linear classifiers