random-forest-regression

Description: Random forest regression is an ensemble of decision trees for regression tasks, averaging the predictions to improve accuracy and control overfitting.

Key Points:

• Reduces overfitting compared to individual decision trees.
• Handles large datasets with higher dimensionality.
• Requires more computational resources.

Applications: Environmental modeling, energy demand forecasting, market analysis.