Could you elaborate where the issue is? You say calling
model.latestModel.clusterCenters.foreach(println) doesn't show an updated
model, but that is just a single statement to print the centers once..
Also, is there any reason you don't predict on the test data like this?
model.predictOnValues(testData.map(lp => (lp.label, lp.features))).print()
On Thu, Feb 18, 2016 at 5:59 PM, ramach1776 <ram...@s1776.com> wrote:
> I have streaming application wherein I train the model using a receiver
> input
> stream in 4 sec batches
>
> val stream = ssc.receiverStream(receiver) //receiver gets new data every
> batch
> model.trainOn(stream.map(Vectors.parse))
> If I use
> model.latestModel.clusterCenters.foreach(println)
>
> the value of cluster centers remain unchanged from the very initial value
> it
> got during first iteration (when the streaming app started)
>
> when I use the model to predict cluster assignment with a labeled input the
> assignments change over time as expected
>
> testData.transform {rdd =>
> rdd.map(lp => (lp.label, model.latestModel().predict(lp.features)))
> }.print()
>
>
>
>
>
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>
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