[SPARK-7383] [ML] Feature Parity in PySpark for ml.features

Implemented python wrappers for Scala functions that don't exist in `ml.features`

Author: Burak Yavuz <[email protected]>

Closes #5991 from brkyvz/ml-feat-PR and squashes the following commits:

adcca55 [Burak Yavuz] add regex tokenizer to __all__
b91cb44 [Burak Yavuz] addressed comments
bd39fd2 [Burak Yavuz] remove addition
b82bd7c [Burak Yavuz] Parity in PySpark for ml.features

Author: brkyvz

mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala

@@ -31,7 +31,7 @@ import org.apache.spark.sql.types.DataType
  * which is available at [[http://en.wikipedia.org/wiki/Polynomial_expansion]], "In mathematics, an
  * expansion of a product of sums expresses it as a sum of products by using the fact that
  * multiplication distributes over addition". Take a 2-variable feature vector as an example:
- * `(x, y)`, if we want to expand it with degree 2, then we get `(x, y, x * x, x * y, y * y)`.
+ * `(x, y)`, if we want to expand it with degree 2, then we get `(x, x * x, y, x * y, y * y)`.
  */
 @AlphaComponent
 class PolynomialExpansion extends UnaryTransformer[Vector, Vector, PolynomialExpansion] {

mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala

@@ -42,7 +42,7 @@ class Tokenizer extends UnaryTransformer[String, Seq[String], Tokenizer] {
 
 /**
  * :: AlphaComponent ::
- * A regex based tokenizer that extracts tokens either by repeatedly matching the regex(default) 
+ * A regex based tokenizer that extracts tokens either by repeatedly matching the regex(default)
  * or using it to split the text (set matching to false). Optional parameters also allow filtering
  * tokens using a minimal length.
  * It returns an array of strings that can be empty.