blending techniques

Blending techniques combine predictions from multiple models or sources to improve overall accuracy and robustness. Think of it like consulting several experts to get a well-rounded opinion—each model might have strengths and weaknesses, and blending leverages their combined insights. Methods include averaging their outputs, weighting them according to reliability, or using a meta-model to learn how best to combine predictions. This approach reduces individual model errors and often results in better performance than relying on a single model, making the final prediction more accurate and reliable.