Random forest regression matlab

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Random forest regression matlab

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Random forest regression is a machine learning technique used for regression analysis. It is often used in situations where the relationship between the variables is non-linear and complex.

The random forest algorithm works by building multiple decision trees and combining them to form a "forest". Each decision tree is trained on a random subset of the data, and the final prediction is based on the average of the predictions made by all the trees in the forest.

In Matlab, the random forest regression algorithm can be implemented using the TreeBagger function. This function allows users to specify the number of trees to include in the forest, as well as other parameters such as the size of the random subsets used to train each tree.

Overall, random forest regression in Matlab is a powerful tool for analyzing complex data and making accurate predictions. By leveraging the strengths of multiple decision trees, it is able to provide more accurate results than traditional regression techniques.