Which of the following descriptions is inaccurate in regard to underfitting?
A. Underfitting occurs when a model is too simple to capture the underlying patterns from the data.
B. When underfitting occurs, the model will have high bias and low variance.
C. Increasing the model’s complexity and reducing regularization can address underfitting.
D. An underfit model performs well with the training data but performs poorly on new, unseen data.
Answer
D
Explanation:
Underfitting means the model performs poorly on both the training data and the unseen test data because it hasn’t learned enough from the training set.
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