Random Forest
Random Forest is a machine learning algorithm that is used for classification, regression and other tasks. It is an ensemble learning method that combines multiple decision trees to create a forest. Each decision tree is built using a random subset of the training data and a random subset of the features. The final prediction is made by aggregating the predictions of all the decision trees. Random Forest is a powerful algorithm that can handle large datasets with high dimensionality and noisy data. It is also resistant to overfitting and can provide feature importance scores. Random Forest has many applications in various fields such as finance, healthcare, and marketing.
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