I guess your use case is not for real time label classify for unseen data? batch prediction is basically the same as batch eval. see if this example helps?
http://predictionio.incubator.apache.org/templates/recommendation/batch-evaluator/ On Sat, Mar 4, 2017 at 11:56 AM Mars Hall <[email protected]> wrote: > Hi 🐸 folks, > > When using unsupervised learning algorithms (like K-Means) we need to save > the predicted labels (cluster IDs) for the training data back into the > datastore. Ideally, we want to automatically save bulk predictions for the > training data after the model is created, when the RDD/DataFrame of all > that data is already resident in Spark memory. It seems complex & > inefficient to develop a whole separate process that (re)selects all that > training data and then iteratively POSTs to `/queries.json` to get every > prediction… > > Would adding a `bulk_save_predictions()` function to the persistent > model's #save method might be the right place to save predictions back into > the eventdata store? > > How do you folks label the training data from an unsupervised algorithm? > > Any suggestions for making bulk predictions that mesh with PredictionIO's > workflow? > > *Mars Hall > Customer Facing Architect > Salesforce App Cloud / Heroku > San Francisco, California > >
