Description
Vectors in Spark have a compressed method which selects either sparse or dense representation by minimizing storage requirements. Matrices should also have this method, which is now explicitly needed in LogisticRegression since we have implemented multiclass regression.
The compressed method should also give the option to store row major or column major, and if nothing is specified should select the lower storage representation (for sparse).
Attachments
Issue Links
- relates to
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SPARK-17137 Add compressed support for multinomial logistic regression coefficients
- Resolved
- links to