Tag Archives: Ensemble Learning

What is Boosting in Ensemble Learning

In the last post, we have discussed the Bagging technique and learnt how Bagging helps us in reducing the model variance. In this post, we will learn one more technique of Ensemble learning which is Boosting. So let me ask you a question. Suppose you have tried all the possible models and none of them performing as expected. So now what you will do? I will go with Boosting. Got the point?

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What is Bagging in Ensemble Learning

In general, any of the machine learning problems we try to find the best possible optimal model for a given problem. That means finding the best possible model within the given model family, for example, finding the best possible decision tree or finding the best possible KNN model. And if we have more time then we can try all model families available, and come up with the best possible regression model, best possible KNN model, best possible SVM model etc. And among these again select the best possible model, which will be either KNN, SVM or any other.

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