GitHub user catap opened a pull request:
https://github.com/apache/spark/pull/4962
[SPARK-6244] Implement VectorSpace to easy create a complicated feature
vector
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.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/catap/spark vector_space
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/4962.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #4962
----
commit 14417c64a4fe63df60536b5252a2d0fee51184f0
Author: Kirill A. Korinskiy <[email protected]>
Date: 2015-03-10T11:57:28Z
[SPARK-6244] Implement VectorSpace to easy create a complicated feature
vector
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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