October 2017
Beginner to intermediate
572 pages
26h 1m
English
Random forest is another useful ensemble learning method that grows multiple decision trees during the training process. Each decision tree will output its own prediction results corresponding to the input. The forest will use the voting mechanism to select the most voted class as the prediction result. In this recipe, we will illustrate how to classify data using the randomForest package.
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