Mohit Sharma: LinkedIn, Twitter
GitHub Site, Repository
I have a linear model. I add a feature to the model and retrain it.
We can’t comment on significance of a feature with \(R^2\). The \(R^2\) is bound to increase (except collinear features, where it stays the same) as we add more and more features.
The significance of a feature can be interpreted from it’s p value, the lower the p value, the more significant it is.
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