This post is deeply misleading. The problem at hand is not the R-squared metric, it is model overfitting. The use of R-squared does not cause overfitting, it is the lack of model validation and/or regularization.
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This post is deeply misleading. The problem at hand is not the R-squared metric, it is model overfitting. The use of R-squared does not cause overfitting, it is the lack of model validation and/or regularization.
Would you be interested in collaborating? I write about AI Research, ML Engineering and DS as well. My main newsletter- AI Made Simple- is currently at 97K readers- https://artificialintelligencemadesimple.substack.com/
In this article, is the R2 metric being calculated on the training dataset or a holdout dataset?