How to evaluate Regression Models

Publish: 27.12.2023
Updated: 27.12.2023 10:02

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.

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