Hi Gna, there are no utilities yet to do that but you can do it manually. In the end, a model is simply a Flink DataSet which you can serialize to some file. Upon reading this DataSet you simply have to give it to your algorithm to be used as the model. The following code snippet illustrates this approach:
mlr.fit(inputDS, parameters) // write model to disk using the SerializedOutputFormat mlr.weightsOption.get.write(new SerializedOutputFormat[WeightVector], "path") // read the serialized model from disk val model = env.readFile(new SerializedInputFormat[WeightVector], "path") // set the read model for the MLR algorithm mlr.weightsOption = model Cheers, Till On Tue, Mar 29, 2016 at 10:46 AM, Simone Robutti < simone.robu...@radicalbit.io> wrote: > To my knowledge there is nothing like that. PMML is not supported in any > form and there's no custom saving format yet. If you really need a quick > and dirty solution, it's not that hard to serialize the model into a file. > > 2016-03-28 17:59 GMT+02:00 Sourigna Phetsarath <gna.phetsar...@teamaol.com > >: > >> Flinksters, >> >> Is there an example of saving a Trained Model, loading a Trained Model >> and then scoring one or more feature vectors using Flink ML? >> >> All of the examples I've seen have shown only sequential fit and predict. >> >> Thank you. >> >> -Gna >> -- >> >> >> *Gna Phetsarath*System Architect // AOL Platforms // Data Services // >> Applied Research Chapter >> 770 Broadway, 5th Floor, New York, NY 10003 >> o: 212.402.4871 // m: 917.373.7363 >> vvmr: 8890237 aim: sphetsarath20 t: @sourigna >> >> * <http://www.aolplatforms.com>* >> > >
