srowen commented on a change in pull request #26124: [SPARK-29224][ML]Implement
Factorization Machines as a ml-pipeline component
URL: https://github.com/apache/spark/pull/26124#discussion_r336802383
##########
File path: python/pyspark/ml/regression.py
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@@ -2126,6 +2127,181 @@ def __repr__(self):
return self._call_java("toString")
+@inherit_doc
+class FactorizationMachines(JavaPredictor, HasMaxIter, HasStepSize, HasTol,
HasSolver, HasLoss,
+ JavaMLWritable, JavaMLReadable):
+ """
+ Factorization Machines.
+
+ loss Supports:
+
+ * logisticLoss (default)
Review comment:
Dumb question but does this render correctly in python docs? I'm not sure
this is how bulleted lists work, but am not sure
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