Random Forest in Bytes
Photo by Jens Lelie on Unsplash This is the second post in In Bytes series. Refer this link to read about the first post. Random Forest: Random forest is an ensemble made by the combination of a large number of decision trees. Ensemble: An ensemble means a group of things viewed as a whole rather than individually. In ensembles, a collection of models is used to make predictions, rather than individual models. In principle, ensembles can be made by combining all types of models. An ensemble can have a logistic regression, a neural network, and few decision trees working in unison. While choosing the model , we need to check for two things- Diversity and Acceptability. Diversity ensures that the models serve complementary purposes, which means that the individual models make predictions independent of each other. The advantages of this are different depending on the type of ensemble. Diversity ensures that even if some trees overfit, the other trees in the ensemb...
