classifier ensemble

A classifier ensemble combines multiple individual models (classifiers) to make a decision about data, such as recognizing objects or categorizing emails. Instead of relying on a single model, it merges the outputs of several, leveraging their diverse strengths and compensating for their weaknesses. This collaborative approach often results in more accurate and robust predictions, much like a panel of experts providing a more reliable opinion than any single person. By integrating different perspectives, ensemble classifiers improve overall performance and handle complex tasks more effectively.