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From Georg Heiler <georg.kf.hei...@gmail.com>
Subject Re: [Spark ML] Positive-Only Training Classification in Scala
Date Mon, 15 Jan 2018 19:55:06 GMT
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 <jornfranke@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 <matt@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>
>
>

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