Answer Posted / Franklin Eric Kujur

The trade-off between bias and variance refers to a common problem in machine learning where finding a model with low bias (simple models that make fewer assumptions) can result in high variance (models that fit noise instead of underlying trends), while finding a model with low variance (complex models that capture underlying patterns) can lead to high bias (models that fail to generalize well to unseen data).

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