Hands-On Machine Learning with C++

Accuracy

One of the most obvious classification metrics is accuracy:

This provides us with a ratio of all positives predictions to all others. In general, this metric is not very useful because it doesn't show us the real picture in terms of cases with an odd number of classes. Let's consider a spam classification task and assume we have 10 spam letters and 100 non-spam letters. Our algorithm predicted 90 of them correctly as non-spam and classified only 5 spam letters correctly. In this case, accuracy will have the following value:

However, ...