I'm not sure whether k-means would converge with this customized
distance measure. You can list (weighted) time as a feature along with
coordinates, and then use Euclidean distance. For other supported
distance measures, you can check Derrick's package:
http://spark-packages.org/package/derrickburns/generalized-kmeans-clustering.
-Xiangrui
On Mon, May 18, 2015 at 2:30 AM, Pa Rö <paul.roewer1...@googlemail.com> wrote:
> hallo,
>
> i want cluster geo data (lat,long,timestamp) with k-means. now i search for
> a good core function, i can not find good paper or other sources for that.
> to time i multiplicate the time and the space distance:
>
> public static double dis(GeoData input1, GeoData input2)
> {
> double timeDis = Math.abs( input1.getTime() - input2.getTime() );
> double geoDis = geoDis(input1, input2); //extra function
> return timeDis*geoDis;
> }
>
> maybe someone know a good core function for clustering temporal geo data?
> (need citation)
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