Skill

Random Forest Algorithm

Data Science, Analytics and AI/ML

Random Forest is a supervised machine learning algorithm that builds an ensemble of decision trees during training and outputs the mode (classification) or mean (regression) of individual trees' predictions. It reduces overfitting compared to a single decision tree by introducing randomness in both data sampling and feature selection. Data scientists and analysts use it widely for classification and regression tasks because it handles nonlinear relationships well and provides feature importance rankings.

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• scikit-learn
• XGBoost
• Feature Engineering
• Decision Trees