Github user feynmanliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/8752#discussion_r39559560
--- Diff: docs/ml-features.md ---
@@ -123,12 +123,21 @@ for features_label in rescaledData.select("features",
"label").take(3):
## Word2Vec
-`Word2Vec` is an `Estimator` which takes sequences of words that
represents documents and trains a `Word2VecModel`. The model is a `Map(String,
Vector)` essentially, which maps each word to an unique fix-sized vector. The
`Word2VecModel` transforms each documents into a vector using the average of
all words in the document, which aims to other computations of documents such
as similarity calculation consequencely. Please refer to the [MLlib user guide
on Word2Vec](mllib-feature-extraction.html#Word2Vec) for more details on
Word2Vec.
+`Word2Vec` is an `Estimator` which takes sequences of words representing
documents and trains a
+`Word2VecModel`. The model maps each word to a unique fixed-size vector.
The `Word2VecModel`
+transforms each document into a vector using the average of all words in
the document; this vector
+can then be used for as features for prediction, document similarity
calculations, etc.
+Please refer to the [MLlib user guide on
Word2Vec](mllib-feature-extraction.html#Word2Vec) for more
+details.
-Word2Vec is implemented in
[Word2Vec](api/scala/index.html#org.apache.spark.ml.feature.Word2Vec). In the
following code segment, we start with a set of documents, each of them is
represented as a sequence of words. For each document, we transform it into a
feature vector. This feature vector could then be passed to a learning
algorithm.
+In the following code segment, we start with a set of documents, each of
which is represented as a sequence of words. For each document, we transform it
into a feature vector. This feature vector could then be passed to a learning
algorithm.
<div class="codetabs">
<div data-lang="scala" markdown="1">
+
+Refer to the [Word2Vec Scala
docs](api/scala/index.html#org.apache.spark.ml.feature.Word2Vec)
--- End diff --
The classname is \`backticked\` in ChiSqSelector but not here or in
Binarizer, we should choose one and be consistent. I would vote for backticking
everything since that's what I've been doing
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