What Does Cross-Validation Mean?
Cross-validation is a statistical approach for determining how well the results of a statistical investigation generalize to a different data set.
Cross-validation is commonly employed in situations where the goal is prediction and the accuracy of a predictive model’s performance must be estimated.
We explored different stepwise regressions in a previous article and came up with different models, now let’s see how cross-validation can help us choose the best model.
Which model is the most accurate at forecasting?
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