Error rate refers to the proportion of incorrect predictions made by a predictive model compared to the total number of predictions. It serves as a crucial metric for assessing the performance of models in terms of their accuracy, which can influence decision-making and business strategies. A lower error rate indicates a more reliable model, while a higher error rate suggests that the model may need refinement or adjustments to improve its predictive capabilities.
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