Thanks Tom. That's clear now. Sent from my phone - sorry to be brief and potential misspell.
*The set of independent regressions described in Wikipedia is *not* an OvR
model.* It is just a (weird) way to understand the multinomial logistic
regression model.
OvR logistic regression and multinomial logistic regression are two
different models.
In multinomial logistic regression as a set of
Still haven't had a chance to read it, but ROC for binary classification
anyway? Also, i.i.d. assumptions are typical for the learning algorithms as
well.
Best,
Sebastian
> On Feb 7, 2019, at 10:15 AM, josef.p...@gmail.com wrote:
>
> Just a skeptical comment from a bystander.
>
> I only skimm
I was earlier looking at the code of predict_proba of LDA and
LogisticRegression. While we certainly some bugs I was a bit confused and I
thought an email would be better than opening an issue since that might not
be one.
In the case of multiclass classification, the probabilities could be
compute
Just a skeptical comment from a bystander.
I only skimmed parts of the article. My impression is that this does not
apply (directly) to the regression setting.
AFAIU, they assume that all observations have the same propability.
To me it looks more like the literature on testing of or confidence
i
Hey Stefan.
I would expect that to depend on the prior.
It could either be a bug or an issue with the variational inference.
Maybe comparing against an MCMC implementation might be helpful?
Though if that works, I'm not sure what the conclusion would be tbh.
(I hate debugging variational inferenc
The paper definitely looks interesting and the authors are certainly
some giants in the field.
But it is actually not widely cited (139 citations since 2005), and I've
never seen it used.
I don't know why that is, and looking at the citations there doesn't
seem to be a lot of follow-up work.
