It involves combining multiple models to improve the accuracy of predictions. It is often used in classification and regression problems where the models have different strengths and weaknesses.
It involves combining multiple models to improve the accuracy of predictions. It is often used in classification and regression problems where the models have different strengths and weaknesses.