A Simple Guide to Ensemble Methods (Simplified ML)
Ensemble Learning in Machine Learning: Why One Model Is Not Enough In our lives we do not usually depend on just one person's opinion when we have to make big decisions. For example, when we are choosing a doctor or investing our money or buying a car we often thing about what many people have to say. Machine Learning is similar. It uses something called Ensemble Learning. We do not just use one model. Ensemble methods use models together to make better predictions that we can trust. What is Ensemble Learning? Ensemble Learning is a way of combining models, usually weak ones to make a stronger model. Think of it like this: it is like having a team of experts of just one expert. Each model helps make the decision, which reduces mistakes and make it more accurate. Types of Ensemble Methods There are three ways to do Ensemble Learning: 1. Bagging - Bagging tries to reduce the differences in the models by training models at the same time. It takes samples of the data and replaces them....