Right -as long as the elements of the stream are (for example) Array[Double] you should be able to make a prediction on each point if you trained the SVM on LabeledPoint examples that are comparable to what you're getting with the DStream.
> On Nov 26, 2013, at 11:00 PM, prabeesh k <[email protected]> wrote: > > Hi Evan, > Actually the input data for prediction is streaming data. In spark > example training data is RDD. But want to predict the model using > Dstream(streaming data). I think it is impossible to train the the model > using streaming data. So are we able to train SVM using static data and > predictions using Streaming data. > > >> On Wed, Nov 27, 2013 at 12:18 PM, Evan Sparks <[email protected]> wrote: >> Hi Prabeesh, >> >> Once you have an SVM model trained, you can make predictions with the model >> (via the model's .predict() method) with any new input data as long as it's >> in the same format that the model was trained with. >> >> - Evan >> >> > On Nov 26, 2013, at 10:03 PM, prabeesh k <[email protected]> wrote: >> > >> > Hi All, >> > Is it possible SVM prediction with DStream data. The SVM model is >> > trained using RDD after that is there any possibility to use Dstream data >> > for prediction. I am not that much aware of SVM. >> > Please suggest. >> > >> > Thanks in Advance. >> > >> > Ragards, >> > Prabeesh >> > >> > >> > >
