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Bias-Variance Tradeoff - What is the difference between bias and variance tradeoff in machine learning?


In the context of machine learning, bias refers to the scenario where an applied algorithm fails to accurately fit the model. On the other hand, variance represents the degree to which the estimation of the target function would alter if different training data is employed. Essentially, it's the discrepancy between the real values and the predicted ones.