How does a model with very high capacity tend to shape its decision boundary during training?
Answer
It twists and turns its decision boundary to perfectly encompass nearly every single training point, including noise and outliers.
When a model has excessive flexibility, it can afford to find highly specific rules for individual training instances, causing its boundary to snake precisely around every data point rather than generalizing the overall pattern.
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