### Why are the changes needed?
Several Spark ML components already allow setting of an initial model, including KMeans, LogisticRegression, and GaussianMixture. This is useful to begin training from a known reasonably good model.
However, the method in LogisticRegression is private to Spark. I don't see a good reason why it should be as the others in KMeans et al are not.
None of these are exposed in Pyspark, which I don't necessarily want to question or deal with now; there are other places one could arguably set an initial model too, but, here just interested in exposing the existing, tested functionality to callers.
### Does this PR introduce _any_ user-facing change?
Other than the new API method, no.
### How was this patch tested?
Existing tests
Closes#33710 from srowen/SPARK-36481.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
71fe0944e8