 value `\(\hat{Y_i}\)`.

**[Statistical learning](#learning)**
- Supervised vs. unsupervised learning.
- Regression vs. classification.
&lt;!-- - Reducible vs. irreducible error. --&gt;
]
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**[Model accuracy](#accuracy)**
- Models can be assessed using loss functions that combine prediction errors.
- For regression problems, MSE is the most common loss function.
- Using separate testing and training data avoids overfitting.

**[Cross-validation](#resampling)**
- Resampling methods avoid overfitti