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user1172468
user1172468
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Are there heuristics/techniques that can be employed to guard against overfitting of a model that do not require/employ human inspectiondo not require/employ human inspection of the learned model's performance.

So for example, they would look at the performance of a predictor and come up with a score of how likely it is that the model has been overfit.score of how likely it is that the model has been overfit.

Are there heuristics/techniques that can be employed to guard against overfitting of a model that do not require/employ human inspection of the learned model's performance.

So for example, they would look at the performance of a predictor and come up with a score of how likely it is that the model has been overfit.

Are there heuristics/techniques that can be employed to guard against overfitting of a model that do not require/employ human inspection of the learned model's performance.

So for example, they would look at the performance of a predictor and come up with a score of how likely it is that the model has been overfit.

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user1172468
user1172468
  • 2.1k
  • 6
  • 26
  • 37

Looking for automatic heuristics/techniques that can produce a measure for overfitting

Are there heuristics/techniques that can be employed to guard against overfitting of a model that do not require/employ human inspection of the learned model's performance.

So for example, they would look at the performance of a predictor and come up with a score of how likely it is that the model has been overfit.