Let's now imagine we want to build a classifier that takes a person's height and weight and assigns a probability to their being Male or Female. We will reuse the height and weight data introduced earlier in this chapter. Let's start by plotting the dataset:
Height versus weight data for 181 men and women
There are many different algorithms for classification. A first glance at the data shows that we can, approximately, separate men from women by drawing a straight line across the plot. A linear method is therefore a reasonable initial attempt at classification. In this section, we will use logistic regression to build a classifier.
A detailed explanation of logistic regression is beyond the scope of this book. The reader unfamiliar with logistic regression is referred to The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman. We will just give a brief summary here.
Logistic regression estimates the probability of a given height and weight belonging...
