What is better: gradient-boosted trees, or a random forest? - FastML
Folks know that gradient-boosted trees generally perform better than a random forest, although there is a price for that: GBT have a few hyperparams to tune, while random forest is practically tuning-free. Let’s look at what the literature says about how these two methods compare. Supervised learning in 2005 In 2005, Caruana et al. made an empirical comparison of supervised learning algorithms [vi
Tree Based Algorithms: A Complete Tutorial from Scratch (in R & Python)
Introduction Tree based algorithms are considered to be one of the best and mostly used supervised learning methods. Tree based algorithms empower predictive models with high accuracy, stability and ease of interpretation. Unlike linear models, they map non-linear relationships quite well. They are adaptable at solving any kind of problem at hand (classification or regression). Methods like tree m
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http://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf
