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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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Machine learning, overfitting and artificial sample increments (LASSO, Boosting)

I thought to increase the number of observations, simply, making a dataset with 30.000 observation, deriving from the five copies of original observations. Are you saying you simply multiplied th …
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