Random forest machine learning is an algorithm that consists of many decision trees.
In the Random Forest model, there are more than one decision tree models.
Random forest algorithm can be used for both classification and regression problems.
Prediction using Random forest classification model
Classification: Each individual tree in the random forest classification, predicts a class and the class with the most votes becomes the model’s prediction
Regression: A prediction from the Random Forest Regressor is an average of the predictions produced by the trees in the given random forest model.
If you like to know what is Random in Random Forest Machine Learning Algorithm, Please watch the below video.
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