Voting Classifier

A Voting Classifier is a method in machine learning that combines the predictions from multiple individual models to make a final decision. Each model votes for a particular outcome, such as whether an email is spam or not. The outcome with the most votes is chosen. This approach improves accuracy because different models may excel in different aspects, compensating for each other’s weaknesses. By aggregating their predictions, the Voting Classifier can provide a more reliable and robust outcome than any single model. It's like getting a consensus from a group rather than relying on just one opinion.