Github user dbtsai commented on the issue:
https://github.com/apache/spark/pull/14834
@sethah For sparse MLOR problems with L1, the models will be sparse in row.
As a result, in the sparse, we need to store the models in CSR format, and CSR
models can be used for model prediction with potential speedup (although we
need to do benchmark and see how much speed up we get). Let's have a separate
PR to implement `compressed` option in matrix. This will be a little bit
complicated. By default, `compressed` has to determine `CSR` or `CSC` will be
used depending on the compression rate. Users need to have a option to choose
the format as well.
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