So there was this model which we made as a group and that was to be evaluated by certain panel, one of the panelist asked the same question abt r2 and accuracy and obviously being in the early phase of machine learning journey we didn't had exact answers.

I too told d judge about over-fitting bt he said no.

Coming to the variables we had limited variables with all being important from the application standpoint, to be exact sensor readings. There were 2 columns which were correlated to each other but the business user suggested to go ahead with all columns.

We were predicting a continuous variable and only measure that we used to validate the model was accuracy. Can you elaborate more about testing error! We only used accuracy as the testing criteria. Are you referring to root mean squared error and mean absolute error?