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Results tagged with overfitting
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user 101070
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.
52
votes
Accepted
Why is xgboost overfitting in my task? Is it fine to accept this overfitting?
Those definition are very similar to the definitions of underfitting and overfitting. … The model is overfitting if the test error is higher than the training error. This means that the model is too complex. …
- 3,751
6
votes
Accepted
random forest - summarize two features in one without losing information
No, you can not reduce overfitting without reducing the information your algorithm can use, this is the whole point of overfitting! … If you want to reduce overfitting, using random forests, you can
Increase the number of trees you grow
Grow shallower trees
Reduce the number of features that are tried for each split
And acting on …
- 3,751