Business Forecasting
Boosting is a machine learning ensemble technique that aims to improve the accuracy of predictive models by combining the outputs of multiple weak learners into a single strong learner. This method sequentially applies weak models to the data, focusing on correcting the errors made by previous models, resulting in enhanced predictive performance. By aggregating predictions from these weak learners, boosting effectively reduces bias and variance, making it a powerful approach in various forecasting tasks.
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