Bagging and Boosting with Equivalent Space Consumption
Rishabh Agarwal, Satwik Mishra, C.S Arjun · 2017
There are various bagging techniques of which Random Forests and Extra Trees are among the most popular. Similarly, AdaBoost and Gradient Boosting are the most common boosting techniques. There is a lot of discussion as to which machine is better and why and which one should be used with different experts having different opinions and the choice based mostly on the problem and personal choice. But the question is how to effectively compare them since bagging and boosting machines, although being ensemble methods, construct their component estimators differently. This paper aims to compare their respective accuracy and time requirement when all the four considered machines use the same number of trees, with all of these trees having the same size by applying them on a randomly generated uniformly distributed data set to remove any chance of a particular machine providing better results on some standard data set