Random Forest
A random forest is a machine learning model that combines many decision trees, each trained on random samples of the data and features, and averages or votes across their predictions.
What is Random Forest?
Averaging many varied trees reduces overfitting and usually gives more accurate and stable results than one tree. Random forests remain widely used for structured business data such as credit scoring and churn prediction.
How it works
Each tree sees a bootstrap sample of the data and a random subset of features at each split; the forest's answer is the majority vote or average.
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