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Results tagged with overfitting
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user 361202
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.
0
votes
What is overfitting while building model?
I like this simple mathematical explanation for the regression case so I'll leave it here:
Overfitting is a consequence of an imbalance between the following three factors:
Number of training samples …
- 351
3
votes
Accepted
Is it possible to have a higher train error than a test error in machine learning?
Overfitting means that a model fits too closely to the training samples so that it fails to generalize (d is comparable to N): train error is low, test error is high. …
- 351