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TitleTypeExcerpt
AdaBoost Page * Short for Adaptive Boosting, AdaBoost is another ensemble algorithm. ## Differences with decision trees * In random forests, we built complete trees each time, but in AdaBoost, each tree only consists of a node and two leaves (which is called a stump). * Another difference to RF is that...
Gradient-boosted trees Page ## Gradient-boosted trees * This algorithm can also be used for regression and classification. * It builds trees one after another, each new tree fixing the problems of the previous one. * It involves no randomization by default. * It uses shallow trees (maximum depth about 5). Therefore requires less...
Random Forests Page ## Ensemble algorithms * Random forests is an ensemble algorithm. * They combine multiple ML algorithms to create a more powerful one. * In competitions, ensemble algorithms are usually the winners. * Two most common ensemble algorithms are _random forests_ and _gradient boosted decision trees_. ## Random forests * A...