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Results tagged with overfitting
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user 1641
For questions related to the concept of overfitting in machine learning, which can be loosely defined as the gap between the performance on the training set and the performance on the test set.
3
votes
Accepted
How to overcome overfitting to single player styles in reinforcement learning?
Both of the solutions you suggest seem to be built around the intuition that it's good to ensure that there is sufficient variety in the experiences that you provide to your RL algorithm.
That intuit …
- 10.5k
19
votes
Accepted
Why do you not see dropout layers on reinforcement learning examples?
Is there other mechanisms to try and deal with overfitting? Or in many RL examples does it not matter? … So, when we're using the evaluation methodology described above, indeed we are overfitting to one specific environment, but overfitting is good rather than bad according to our evaluation criteria. …
- 10.5k
4
votes
How does rotating an image and adding new 'rotated classes' prevent overfitting?
How can data augmentation reduce overfitting? … "Overfitting" can have a slightly different interpretation in the case of one-shot learning than in traditional learning. …
- 10.5k