This error measure evaluates performance consistency during a series of trials. A) AE B) CE C) VE D) E

Question

Quizplus · Accepted Answer

VE stands for Variance Explained, which measures the consistency of the model's predictions across a series of trials. It is a useful error measure in situations where consistency is more important than accuracy. AE (Absolute Error) and CE (Classification Error) are ways to measure accuracy, while E is not an error measure at all.

This Error Measure Evaluates performance Consistency During a Series of Trials