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The regression routines should allow the user to choose the distribution of liking. For now, we cannot distinguish Laplace and Gaussian distributions as we rely on the number of parameters to choose the corresponding distributions.
Implement at least the following distributions: Dirac (standard), Gaussian, Laplace, NIG
A potential solution was highlighted in this discussion:
"""
I had the same kind of problem with another project of mine, I would suggest creating a function like this:
I think it could be interesting to use the Distribution class from Pytorch, but it might be too much. A dictionary with the parameters should do it nicely too.
"""
alafage
changed the title
Enable custom distributions for probabiilistic regression
Enable custom distributions for probabilistic regression
Oct 11, 2023
o-laurent
changed the title
Enable custom distributions for probabilistic regression
✨ Enable custom distributions for probabilistic regression
Oct 18, 2023
The regression routines should allow the user to choose the distribution of liking. For now, we cannot distinguish Laplace and Gaussian distributions as we rely on the number of parameters to choose the corresponding distributions.
A potential solution was highlighted in this discussion:
"""
I had the same kind of problem with another project of mine, I would suggest creating a function like this:
I think it could be interesting to use the
Distribution
class from Pytorch, but it might be too much. A dictionary with the parameters should do it nicely too."""
Originally posted by @alafage in #46 (comment)
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