How to evaluate Regression Models

You can easily build up a regression model for a data set, additionally you need to evaluate the success of your model. Here you can find methods of evaluation:

1. Mean Absolute Error (MAE): This is the average of the absolute errors between predicted and actual values. It gives a straightforward measure of average error magnitude. The formula is:MAE=1n∑i=1n∣yi−y^i∣MAE=n1​i=1∑n​∣yi​−y^​i​∣where yiyi​ is the actual value, y^iy^​i​ is the predicted value, and nn is the number of samples.