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 ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
