Hi Hilmi,

I think in your case it makes sense to define a custom vector of strings.
The easiest implementation could be an Array[String] or List[String].

The reason why it does not make so much sense to make Vector and DenseVector
generic is that these types are algebraic data types. How would you define
algebraic operations such as scalar product, outer product, multiplication,
etc. on a vector of strings? Then you would have to provide different
implementations for the different type parameters.

Cheers,
Till
​

On Mon, Jan 18, 2016 at 1:40 PM, Hilmi Yildirim <hilmi.yildi...@dfki.de>
wrote:

> Hi,
> how I explained it in a previous E-Mail, I need a LabeledVector where the
> label is also a vector. After we discussed this issue, I created a new
> class named LabeledSequenceVector with the labels as a Vector. In my use
> case, I want to train a POS-Tagger system, so the "vector" is a vector of
> strings and the "labels" is also a vector of strings. If I use the Flink
> Vector/DenseVector implementation then the vector does only have double
> values but I need String values.
>
> Best Regards,
> Hilmi
>
>
> Am 18.01.2016 um 13:33 schrieb Chiwan Park:
>
>> Hi Hilmi,
>>
>> In NLP, which types are used for vector values? I think we can cover
>> typical case using double values.
>>
>> On Jan 18, 2016, at 9:19 PM, Hilmi Yildirim <hilmi.yildi...@dfki.de>
>>> wrote:
>>>
>>> Hi,
>>> the Vector and DenseVector implementations of Flink ML only allow Double
>>> values. But there are cases where the values are not Doubles, e.g. in NLP.
>>> Does it make sense to make the implementations generic, i.e. Vector[T] and
>>> DenseVector[T]?
>>>
>>> Best Regards,
>>> Hilmi
>>>
>>> --
>>> ==================================================================
>>> Hilmi Yildirim, M.Sc.
>>> Researcher
>>>
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>> Chiwan Park
>>
>>

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