In machine learning, variance refers to the extent to which a model's predictions vary for a given data point. High variance often indicates an overly complex model that models noise in the training data, leading to overfitting.
Variance in Model Performance
Variance is one part of the bias-variance tradeoff, a fundamental concept in machine learning. A model with high variance pays too much attention to the training data and does not generalize well to new data. The goal is to balance bias (underfitting) and variance (overfitting) for optimal model performance.
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