As far as I know spark does not implement such algorithms. In case the dataset is small http://scikit-learn.org/stable/modules/generated/sklearn.svm.OneClassSVM.html might be of interest to you.
Jörn Franke <jornfra...@gmail.com> schrieb am Mo., 15. Jan. 2018 um 20:04 Uhr: > I think you look more for algorithms for unsupervised learning, eg > clustering. > > Depending on the characteristics different clusters might be created , eg > donor or non-donor. Most likely you may find also more clusters (eg would > donate but has a disease preventing it or too old). You can verify which > clusters make sense for your approach so I recommend not only try two > clusters but multiple and see which number is more statistically > significant . > > On 15. Jan 2018, at 19:21, Matt Hicks <m...@outr.com> wrote: > > I'm attempting to create a training classification, but only have positive > information. Specifically in this case it is a donor list of users, but I > want to use it as training in order to determine classification for new > contacts to give probabilities that they will donate. > > Any insights or links are appreciated. I've gone through the documentation > but have been unable to find any references to how I might do this. > > Thanks > > ---*Matt Hicks* > > *Chief Technology Officer* > > 405.283.6887 <(405)%20283-6887> | http://outr.com > > <logo 2 small.png> > >
