Voting Classifier — Machine Learning Model | Quick Tutorial

There are tons of classification machine learning algorithms currently present to use.

In this story I am going to discuss Voting Classifier. So lets get into it!

Voting Classifier (Image Credit: Youtube)

What is Voting Classifier

A voting classifier is a machine learning estimator that trains various base models or estimators and predicts on the basis of aggregating the findings of each base estimator.

When to use it?

• All models in the ensemble have generally the same good performance.
• All models in the ensemble mostly already agree.

Types of Voting Classifiers

1. Hard Voting: In hard voting, the predicted output class is a class with the highest majority of votes i.e the class which had the highest probability of being predicted by each of the classifiers.
2. Soft Voting: In soft voting, the output class is the prediction based on the average of probability given to that class.

In short, Hard voting is for models that predict class labels and Soft voting is for models that predict class membership probabilities.

Python implementation of Voting Classifier