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Modeling error (especially sampling error) instead of replicable and informative relationships among variables improves model fit statistics, but reduces parsimony, and worsens explanatory and predictive validity.

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How to reduce overfitting in linear regression

In my opinion, this approach can help reduce overfitting. It is called locally weighted regression (LWR). …
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