[jira] [Updated] (FLINK-1718) Add sparse vector and sparse matrix types to machine learning library

["Till Rohrmann (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-1718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Till Rohrmann updated FLINK-1718:
---------------------------------
    Issue Type: New Feature  (was: Improvement)

> Add sparse vector and sparse matrix types to machine learning library
> ---------------------------------------------------------------------
>
>                 Key: FLINK-1718
>                 URL: https://issues.apache.org/jira/browse/FLINK-1718
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>              Labels: ML
>
> Currently, the machine learning library only supports dense matrix and dense vectors. For future algorithms it would be beneficial to also support sparse vectors and matrices.
> I'd propose to use the compressed sparse column (CSC) representation, because it allows rather efficient operations compared to a map backed sparse matrix/vector implementation. Furthermore, this is also the format the Breeze library expects for sparse matrices/vectors. Thus, it is easy to convert to a sparse breeze data structure which provides us with many linear algebra operations.



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