A

Admin • 833.24K Points
Coach

Q. The average squared difference between classifier predicted output and actual output.

  • (A) mean squared error
  • (B) root mean squared error
  • (C) mean absolute error
  • (D) mean relative error

Explanation by: Admin

The measure described, which represents the average squared difference between the predicted output of a classifier and the actual output, is known as Option A: mean squared error. Mean squared error is a common metric used to evaluate the performance of machine learning models, with lower values indicating better predictive accuracy.

You must be Logged in to update hint/solution

Discusssion

Login to discuss.

Be the first to start discuss.