When several classifiers give different answers, choose the class predicted by the greatest number of learners. This is the mode of their predictions; if classes tie, choose randomly. section 12.1
Three tree votes
For an input, three depth-1 decision trees each predict 0 or 1. The combined classifier returns whichever value receives more votes. section 12.2
Figure 12.6 The way to obtain the predictions of the random forest is by combining the predictions of the three weak learners. On the top, we can see the three boundaries of the decision trees from figure 12.5. On the bottom, we can see how the three decision trees vote to obtain the boundary of the corresponding random forest.
Compare the individual tree boundaries with the combined boundary formed by their votes. section 12.2
