Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/10242#discussion_r54696423
--- Diff: python/pyspark/ml/clustering.py ---
@@ -291,6 +292,284 @@ def _create_model(self, java_model):
return BisectingKMeansModel(java_model)
+class LDAModel(JavaModel):
+ """ A clustering model derived from the LDA method.
+
+ Latent Dirichlet Allocation (LDA), a topic model designed for text
documents.
+ Terminology
+ - "word" = "term": an element of the vocabulary
+ - "token": instance of a term appearing in a document
+ - "topic": multinomial distribution over words representing some
concept
+ References:
+ - Original LDA paper (journal version):
+ Blei, Ng, and Jordan. "Latent Dirichlet Allocation." JMLR, 2003.
+
+ .. versionadded:: 2.0.0
+ """
+
+ @since("2.0.0")
+ def isDistributed(self):
+ """Indicates whether this instance is of type
DistributedLDAModel"""
+ return self._call_java("isDistributed")
+
+ @since("2.0.0")
+ def vocabSize(self):
+ """Vocabulary size (number of terms or terms in the vocabulary)"""
+ return self._call_java("vocabSize")
+
+ @since("2.0.0")
+ def topicsMatrix(self):
+ """Inferred topics, where each topic is represented by a
distribution over terms."""
+ return self._call_java("topicsMatrix")
--- End diff --
The Python API doc should consistent with Scala one, should also include
the ```WARNING``` to tell users that this API may cause collecting a large
amount of data to the driver.
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