High variance refers to a situation where a statistical model's predictions fluctuate widely, indicating that the model is too complex and sensitive to the training data. This often leads to overfitting, where the model captures noise in the data rather than the underlying patterns. As a result, high variance affects the model's ability to generalize well to new, unseen data.
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