Question

If f is the total number of features and n is the number of data points in the training data. A crude estimate of the time taken to build a random forest is proportional to the number of trees times

Answer 1

Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operate by constructing a multitude of decision trees at training time.

Explanation:

• Number of trees should have a good balance between ROC AUC and processing time.
• The optimal number of trees in a random forest depends on the number of predictors only in extreme cases.
• The algorithm method used to calculate the number of trees in the random forest.
• If we increase the depth of tree it will cause overfitting.
• Learning rate is not an hyperparameter in random forest.
• Increase in the number of tree will cause under fitting.

To Learn More...

1.If we do not define number of trees to be built in random forest then how many trees random forest internally creates?

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