What is random forest? What it is called random?

Question

Accepted Answer

Random forest is an ensemble learning method used for classification and regression tasks, consisting of multiple decision trees.

Random forest is made up of multiple decision trees, where each tree is built using a subset of the training data and a random subset of features.
During prediction, each tree in the forest independently predicts the output, and the final output is determined by a majority vote (classification) or averaging (regression) of all the trees' predictions.
Random forest is known for its high accuracy, robustness to overfitting, and ability to handle large datasets with high dimensionality.
Example: In a random forest model for predicting customer churn, each decision tree may consider different features such as customer age, purchase history, and website interactions.

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