Building Intuition for Random Forests
Random Forest — A group of decision trees — is a powerful machine learning algorithm
It is intriguing to see how simply and easily a random forest can yield extremely useful results. Random Forest is a supervised machine learning algorithm.
Random Forests are essentially an ensemble of decision trees. In its simplest form a Decision tree is a sequence of choices.
As far as accuracies of prediction go Decision Trees are quite inaccurate. Even one mis-step in the choice of the next node, can lead you to a completely different end. Choosing the right branch instead of the left could lead you to the furthest end of the tree. You would be off by a huge margin!
A huge number of decision trees created randomly using input data comprise the Random Forest. The randomness of creation combined with simplicity of a Decision Tree lends Random Forests their awesomness!
Random Forests = Simplicity of DT + Accuracy Through Randomness
