= Random forest
{wiki=Random_forest}
Random forest is a popular machine-learning algorithm that belongs to the family of ensemble methods. It is primarily used for classification and regression tasks. The key idea behind random forests is to combine multiple decision trees to create a more robust and accurate model. Here’s how it works: 1. **Ensemble Learning**: Random forest builds multiple decision trees (hence the term "forest") during training and merges their outputs to improve predictive accuracy and control overfitting.
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