U may want to use FlinkMLTools.persist() methods which use
TypeSerializerFormat and don't enforce IOReadableWritable.
On Tue, Mar 29, 2016 at 2:12 PM, Sourigna Phetsarath <
gna.phetsar...@teamaol.com> wrote:
> Till,
>
> Thank you for your reply.
>
> Having this issue though, WeightVector does not extend IOReadWriteable:
>
> *public* *class* SerializedOutputFormat<*T* *extends* IOReadableWritable>
>
> *case* *class* WeightVector(weights: Vector, intercept: Double) *extends*
> Serializable {}
>
>
> However, I will use the approach to write out the weights as text.
>
>
> On Tue, Mar 29, 2016 at 5:01 AM, Till Rohrmann <trohrm...@apache.org>
> wrote:
>
>> 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>*
>>>>
>>>
>>>
>>
>
>
> --
>
>
> *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>*
>
