Hello everyone,

what's needed is not difficult but far from trivial, I can be a co-champ if 
someone wants to work in teams.


Sadly I have my day-to-day job in which I already have to put lots of 
time..........this would be more fun

Cheers!
Demian 


--
Demian Wassermann, PhD
[email protected]
LMI / PNL / SPL Labs
Harvard Medical School
Brigham and Women's Hospital
1249 Boylston, Boston, MA, USA

On Nov 29, 2011, at 7:24 PM, Olivier Grisel wrote:

> 2011/11/29 Kenneth C. Arnold <[email protected]>:
>> On Tue, Nov 29, 2011 at 4:53 PM, Olivier Grisel
>> <[email protected]> wrote:
>>> Now back to you problem I think we should support fitting models with
>>> just one sample just for the sake of consistency / continuity even if
>>> theds is no practical application of fitting models with a single
>>> sample: fitting models  with 2 samples would be almost as stupid as
>>> fitting a model with only one sample and there is no principled or
>>> natural, pre-determined threshold I know of that would give us the
>>> minimum number of samples to provide to an estimator.
>>> 
>>> IMHO this is a bug. GaussianProcess and other scikit-learn estimators
>>> should accept to fit with singleton training sets and provide
>>> predictions that are mathematically consistent even if useless in
>>> practice.
>> 
>> I misspoke earlier: the MLE for a GP conditioned on a single point is
>> just the value at that point, just as the maximum likelihood predictor
>> for a Gaussian fit to one data point is that data point. (The variance
>> is indeed ill-posed, but the prediction is just the mean.)
> 
> That makes sense. Fortunately we don't have an API to compute the
> expected variance of a prediction :)
> 
>> https://github.com/scikit-learn/scikit-learn/pull/97 looks like
>> activity fizzled right as it was about ready to merge. What's the
>> status? [Yes, I'm cautiously expressing and gauging interest without
>> implicitly promising work.]
> 
> Indeed this pull request good forgotten and need a champion to revive
> it: upgrade it to the current status of the master and give a status
> of the pending points that were raised in the previous comments, make
> sure that the documentation is up to date and that the test pass with
> a good coverage.
> 
> -- 
> Olivier
> http://twitter.com/ogrisel - http://github.com/ogrisel
> 
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