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https://issues.apache.org/jira/browse/SPARK-6244?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kirill A. Korinskiy updated SPARK-6244:
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Comment: was deleted
(was: Yes, I agree with you that name Vector Space mayn't correct for this
wrapper and list of vectors sounds better.
I've checked breeze and found vertcat, but this operation support same type of
vector.
In my case I create a feature vector from sparse and dense vectors.)
> Implement VectorSpace to easy create a complicated feature vector
> -----------------------------------------------------------------
>
> Key: SPARK-6244
> URL: https://issues.apache.org/jira/browse/SPARK-6244
> Project: Spark
> Issue Type: New Feature
> Reporter: Kirill A. Korinskiy
>
> VectorSpace is wrapper what implement three operation:
> - concat -- concat all vectors to single vector
> - sum -- sum of vectors
> - scaled -- multiple scalar to vector
>
> Example of usage:
> ```
> import org.apache.spark.mllib.linalg.Vectors
> import org.apache.spark.mllib.linalg.VectorSpace
> // Create a new Vector Space with one dense vector.
> val vs = VectorSpace.create(Vectors.dense(1.0, 0.0, 3.0))
> // Add a to vector space a scaled vector space
> val vs2 = vs.add(vs.scaled(-1d))
> // concat vectors from vector space, result: Vectors.dense(1.0, 0.0, 3.0,
> -1.0, 0.0, -3.0)
> val concat = vs2.concat
> // take a sum from vector space, result: Vectors.dense(0.0, 0.0, 0.0)
> val sum = vs2.sum
> ```
> This wrapper is very useful when create a complicated feature vector from
> structured objects.
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