Which of the following is not true concerning overfitting?
A)It may result from using the training data inappropriately
B)It attempts to describe the random error thereby making the model less useful.
C)It does not violate the law of parsimony.
D)Over fitted models may work poorly when using new data.

Question

Quizplus · Accepted Answer

Overfitting usually leads to models that are overly complex and not parsimonious, which means they may include unnecessary variables or have too much flexibility to fit noise in the data. Therefore, choice C is not true, while the other options are valid descriptions of overfitting.

Which of the Following Is Not True Concerning Overfitting