Weighted Combination

Weighted combination is a technique used in data science and artificial intelligence to combine the predictions of multiple models or algorithms. In this technique, each model is assigned a weight based on its performance on a validation set or cross-validation. The weights are then used to calculate a weighted average of the predictions of all the models. The idea behind this technique is that by giving more weight to the better-performing models, the overall prediction accuracy can be improved. Weighted combination is commonly used in ensemble learning, where multiple models are trained on the same dataset to improve the overall prediction accuracy.
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