Answer Posted / Kundan Kumar

The bias-variance trade-off is a fundamental problem in machine learning that deals with finding the right balance between an overly complex model (high bias and low variance) and an overfitting model (low bias and high variance). A model with high bias makes incorrect assumptions, leading to poor performance on unseen data. On the other hand, a model with high variance fits the training data too closely, also leading to poor performance on unseen data.

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