It is the bias that represents the precision of a model. A model with a high bias tends to be oversimplified and results in insufficient fit. The variance represents the sensitivity of the model to data and noise. A model with high variance results in overfitting.
Therefore, the trade-off between bias and variance is a property of machine learning models in which lower variance leads to higher bias and vice versa. In general, an optimal balance of the two can be found in which error is minimized.
Posted Date:- 2021-10-21 10:29:22
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