random forest

Random Forest is a machine learning algorithm that is used for classification and regression problems. It is an ensemble learning method that creates multiple decision trees at training time and combines their outputs to make the final prediction. Each decision tree is created using a random subset of features and training data, which helps to reduce overfitting and improve accuracy. During prediction, the algorithm takes the average of the outputs of all the decision trees to make its final prediction. Random Forest is widely used in various fields such as finance, healthcare, and image recognition.