Suppose we made the (demonstrably incorrect) prediction that ‘Nobody survived’. Then, since 61% of the passengers died, we would get 61% right in the training set. If we used the slightly more complex prediction rule, ‘All women survive and no men survive’, we would correctly classify 78% of the training set. These naïve rules serve as good baselines from which to measure any improvements obtained from more sophisticated algorithms.
