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From Jörn Franke <jornfra...@gmail.com>
Subject Re: [Spark ML] Positive-Only Training Classification in Scala
Date Mon, 15 Jan 2018 19:04:16 GMT
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 | http://outr.com
> <logo 2 small.png>

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