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Random Forest

Random forest algorithm is a supervised classification and regression algorithm which will randomly create a forest with several trees. Generally, the more trees in the forest, the more robust the forest looks like. Similarly, the higher the number of trees in the forest in the random forest classifier, the greater the accuracy of the results. In simple words, Random forest constructs multiple decision trees and attaches them together to get a more accurate and stable prediction result. The forest it builds is a collection of Decision Trees, trained with the bagging method.

Random Forest Syntax:

Example:

In this section, we will step by step go through a complete Random Forest using the cardio dataset.

Graph Output:

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