Hands-On Ensemble Learning with Python

Hard voting

Hard voting combines a number of predictions by assuming that the most voted class is the winner. In a simple case of two classes and three base learners, if a target class has at least two votes, it becomes the ensemble's output, as shown in the following diagram. Implementing a hard voting classifier is as simple as counting the votes for each target class:

Voting with two classes and three base learners

For example, let's say that there are three different base learners, who are predicting whether a sample belongs to one of three classes with a certain probability (Table 1).

In the following table, each learner predicts the ...