AnswerBun.com

Is it possible to detect overfitting automatically/programmatically after model creation?

Cross Validated Asked by Ayberk Yavuz on December 9, 2020

The definition of overfitting is “the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably” (the model is good at training data and it is bad at test data).

But, is there a way to define overfitting programmatically ? For example; if a classification model’s accuracy/f1 score is between %99 and %90 at training data and the model’s accuracy/f1 score is equal or less than %80 at test data, the model overfits. Or if a regression model’s rmse value is equal or less than 0.7 at training data (target variable ranges from 0 to 1000) and the model’s rmse value is equal or more than 5.0 at test data, the model overfits.

Add your own answers!

Related Questions

How to complete analysis with small N?

2  Asked on December 23, 2021 by jess-jax

   

Which type of regression is most suitable for my situation?

1  Asked on December 23, 2021 by nikolay-bogdanov

   

Ask a Question

Get help from others!

© 2023 AnswerBun.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP