Overfitting refers to
A) placing too much emphasis on the sample-specific noise
B) fitting the model too tightly
C) fitting the model too loosely
D) underestimating model parameters

Name: Overfitting refers to A) placing too much emphasis on the sample-specific noise B) fitting the model too tightly C) fitting the model too loosely D) underestimating model parameters
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Question

Quizplus · Accepted Answer

Overfitting occurs when a model is too closely fit to a particular dataset, resulting in poor performance on new data.

Overfitting Refers to