The technique of random forests, the extension of the approach to the construction of regression trees, was recently proposed by Leo Breiman. Breiman was a distinguished statistician at the University of California, Berkeley.
The random forests algorithm is based on the construction of many regression trees. Every single case is passed through all the trees in the forest; each of them provides a prediction. The final forecast is then made by averaging the predictions provided by individual regression trees. In accordance with what has been said, the tree response is an estimate of the dependent variable given the predictors.
To perform random forests regression, we will use the randomForest() function contained ...
