Random forests were developed by Leo Breiman and Adele Cutler. Their strength in the field of machine learning has been shown nicely in a blog entry at Strata 2012: "Ensembles of decision trees (often known as random forests) have been the most successful general-purpose algorithm in modern times", as they "automatically identify the structure, interactions, and relationships in the data".
Moreover, it has been noticed that "most Kaggle solutions have no less than one top entry that vigorously utilizes this methodology". Random forests additionally have been the preferred algorithm for recognizing the body part in Microsoft's Kinect, which is a movement detecting information gadgets for Xbox consoles and Windows PCs.
Random forests comprises of a group of decision trees. We will consequently begin to analyze decision trees.
A decision tree, as discussed previously, is a tree-like chart where on each node there is a choice, in view of one single feature. Given an arrangement of...
