Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/18035
@yanboliang Appreciate discussing this matter with me, and it is important
to sort this out now. Normally I wouldn't mind either way; but in this case I
kinda feel strongly about not making this name change for 2 main reasons:
- first, the work has been done by a contributor. I feel we are at some
level undoing his work by making this change now after his work is merged,
instead of providing valuable timely feedback during the review process
- second, being concise is important. I understand the popularly of the
search term. Aside from future supportability, naming conflicts etc, I think we
choose to name it
[LinearSVC](http://people.apache.org/~pwendell/spark-nightly/spark-master-docs/spark-2.3.0-SNAPSHOT-2017_05_22_08_01-cfca011-docs/api/scala/index.html#org.apache.spark.ml.classification.LinearSVC)
in Scala because it concisely describes what it does and supports. We could
have named it SVM but we didn't? So I'm not sure we should name it `svm` for R.
We also didn't call boosted tree `gbm` which is hugely popular, but instead
`gbt`. Also, as you are aware, we get a lot of feedback and requests on adding
new ML algorithm support in Spark. I think it is very important to set
expectation in this case so that people does not search and find `svm` but it
doesn't do what people thinks it should do? Unless you think we will go beyond
linear and support polynomial etc. at some point? But I think you agree that is
rather u
nlikely.
Anyway, what do you think?
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