Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes or mean prediction of the individual trees.
To say it in simple words: Random forest builds multiple decision trees and merges them together to get a more accurate and stable prediction.
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