A small guide to Random Forest - part 2

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This is the second part of a simple and brief guide to the Random Forest algorithm and its implementation in R. If you missed Part I, you can find it here. randomForest in R R has a package called randomForest which contains a randomForest function. If you want to explore in depth this implementation, I […]

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A small guide to Random Forest - part 1

I've recently started playing with Kaggle and got curious about one of the most famous classification/regression framework, Random Forest. In a problem of classification or regression, several random decision trees (a "forest") are built and at the end the outputs are combined ("bagging"). The intuition is that randomness and a meaningful quantity of trees will avoid […]

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