Timeline for What is the difference between model and data distributions?
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| Apr 5, 2020 at 15:27 | comment | added | Djib2011 | Generative models is a broad category of ML models including the generator from GANs, naive bayes, etc. The other category are discriminative models, which don't try to explicitly model the data's distribution, i.e. there's no notion of a model's distribution. The terms "generative" and "discriminative" models are widely used, as is the notion of the data-generating distribution. I'm unaware, though, if the latter was coined by Goodfellow or not (it might have also different names). Nowadays, though, it is the only widely-used terminology I'm aware of. | |
| Apr 5, 2020 at 14:09 | comment | added | nbro | This answer seems correct, but why are you talking about generative models? Are model distributions only associated with generative models? Is the terminology "data distribution" and "model distributions" only useful in the case of GANs or generative models? Is this terminology widely known in machine learning, or only Goodfellow's book uses it? | |
| Apr 5, 2020 at 14:09 | history | edited | nbro | CC BY-SA 4.0 |
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| Apr 5, 2020 at 10:40 | history | answered | Djib2011 | CC BY-SA 4.0 |