Random Forest Classifier using sklearn in Python - The Security Buddy

Random forests use an ensemble learning method for classification or regression. A random forest classifier is used to solve classification problems. When we train a random forest with training data, it generates several decision trees. And then, when input features are provided, the random forest selects the class that is selected by most of the trees in the random forest. In our previous articles, we discussed classification trees and regression trees.