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Results tagged with overfitting
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user 328384
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.
1
vote
Cross-validation for (hyper)parameter tuning to be performed in validation set or training set?
I believe you are looking for a hard-rule stating how the data should be distributed. Well it is totally your call. Approach 1 is most widely used, but a better split would be 50% for training, 30% fo …
- 129
0
votes
Why use regularization instead of feature selection for logistic regression?
As you quoted: It seems to me that for logistic regression, the reason of overfitting is always excessive number of features. … If you have the problem of Overfitting in your ML model, you tend to
penalize the features, which are making your model overfit. …
- 129