Mastering Machine Learning with scikit-learn - Second Edition

From Linear Regression to Logistic Regression

In previous chapters, we discussed simple, multiple, and polynomial linear regression. The models are special cases of the generalized linear model, a flexible framework that requires fewer assumptions than ordinary linear regression. In this chapter, we will discuss some of these assumptions as they relate to another special case of the generalized linear model called logistic regression.

Unlike the regression models we have previously discussed, logistic regression is used for classification tasks. Recall that the goal in classification tasks is to induce a function that maps an observation to its associated class or label. A learning algorithm must use pairs of feature vectors and their corresponding ...