VotingClassifiers.md (660B)
1 # Voting Classifiers 2 3 ML D4 4 5 **Definition:** Voting classifiers are ensembles of classification models that use each of their outputs to predict the final output. 6 7 Assume you are ussing an SVM classifier, random forest, and logistic regression, the outputs of these may be computed and then whichever classification gets the most votes is decided to be the output. 8 9 This process aggregates the outputs of the individual models into one output. Majority voting is called hard voting where the most popular output is chosen. 10 11 The alternative to hard voting is soft voting which takes the average of probability outputs from each model to make a determination.