Random Forests

Random Forests is an ensemble learning method that combines multiple decision trees to make predictions.

Random Forests is an ensemble learning method that combines multiple decision trees to make predictions. Each tree in the forest is trained on a random subset of the training data with replacement, and a random subset of features is considered at each split. By aggregating the predictions of individual trees, Random Forests can handle complex datasets, reduce overfitting, and provide robust predictions.