What is random forests

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Random forests is an ensemble learning method used for classification and regression tasks.

Random forests consist of multiple decision trees trained on different subsets of the data.
Each tree in the forest makes a prediction, and the final prediction is the average (regression) or majority vote (classification) of all trees.
Random forests are robust to overfitting and handle high-dimensional data well.
They are widely used in various fields such as finance, healthcare, and marketing.
Example: Random forests can be used to predict customer churn in a telecom company based on various features like call duration, location, and plan type.

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