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4 votes

Is duplicating dataset an augmentation?

Duplicating the dataset without changing anything is a bad idea. It does nothing useful (no augmentation is done, no new information added), but pollutes the out-of-bag (i.e. when you randomly sample ...
Björn's user avatar
  • 33.6k
3 votes

Why RandomForestRegressor.score() return a coefficient of determination?

Wikipedia: the coefficient of determination, denoted $R^2$ or $r^2$ and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the ...
Stephan Kolassa's user avatar
1 vote

Can I use simulated data only for testing a Random Forest regression already trained on real data?

This is generally good practice for understanding many machine learning models, and some complex statistical models. It's especially valuable as a way to evaluate how the model extrapolates. In the ...
mkt's user avatar
  • 19k
1 vote

Is duplicating dataset an augmentation?

I don't think it's reasonable to duplicate existing data and call it data augmentation. Augmentation as I understand it involves some sort of transformation to the data (rotating images, adding noise, ...
mkt's user avatar
  • 19k

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