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I was trying to implement ROSE (Random Oversampling Examples) in Julia, and after considering the paper I decided to look at imbalanced-learn's implementation. There seems to be a shrinkage
parameter that has no mention in the paper. I see that its multiplied by the smoothing matrix used for the kernel as in here near line 214 and understand its effect; however, why the specific name "shrinkage"? Especially when it causes the points to spread farther apart...
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