What is the Mean Squared Error (MSE) in the context of regression models?
- Average of absolute differences between predictions and actuals
- Average of squared differences between predictions and actuals
- Sum of absolute differences between predictions and actuals
- Sum of squared differences between predictions and actuals
The Mean Squared Error (MSE) is the average of the squared differences between the predicted values and the actual values. It's a common metric for evaluating the performance of regression models by giving more weight to larger errors.
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