Random Forest Regressor


Random forest is an ensemble learning method based on the construction of a multitude of decision trees. It solves regression tasks by outputting the averaged prediction of the individual trees.


To use the algorithm you need to specify the learning rate, the number of iterations, the number of leaves.
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  • Note that higher number of leaves leads to increased accuracy, but rises the chances of overfitting.
  • The number of the boosting iterations is suggested to be set inversely to the learning rate (decrease one while increasing second).