Recall from Chapter 1, The Fundamentals of Machine Learning that the goal of classification tasks is to use one or more features to predict the value of a discrete response variable. Let's work through a toy classification problem. Assume that you must use a person's height and weight to predict his or her sex. This problem is called binary classification because the response variable can take one of two labels. The following table records nine training instances:
|
Height |
Weight |
Label |
|
158 cm |
64 kg |
male |
|
170 cm |
66 kg |
male |
|
183 cm |
84 kg |
male |
|
191 cm |
80 kg |
male |
|
155 cm |
49 kg |
female |
|
163 cm |
59 kg |
female |
|
180 cm |
67 kg |
female |
|
158 cm |
54 kg |
female |
|
178 cm ... |
