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-rw-r--r--docs/ml-features.md16
1 files changed, 10 insertions, 6 deletions
diff --git a/docs/ml-features.md b/docs/ml-features.md
index 3db24a3840..3cb26443b9 100644
--- a/docs/ml-features.md
+++ b/docs/ml-features.md
@@ -251,11 +251,12 @@ frequently and don't carry as much meaning.
`StopWordsRemover` takes as input a sequence of strings (e.g. the output
of a [Tokenizer](ml-features.html#tokenizer)) and drops all the stop
words from the input sequences. The list of stopwords is specified by
-the `stopWords` parameter. We provide [a list of stop
-words](http://ir.dcs.gla.ac.uk/resources/linguistic_utils/stop_words) by
-default, accessible by calling `getStopWords` on a newly instantiated
-`StopWordsRemover` instance. A boolean parameter `caseSensitive` indicates
-if the matches should be case sensitive (false by default).
+the `stopWords` parameter. Default stop words for some languages are accessible
+by calling `StopWordsRemover.loadDefaultStopWords(language)`, for which available
+options are "danish", "dutch", "english", "finnish", "french", "german", "hungarian",
+"italian", "norwegian", "portuguese", "russian", "spanish", "swedish" and "turkish".
+A boolean parameter `caseSensitive` indicates if the matches should be case sensitive
+(false by default).
**Examples**
@@ -346,7 +347,10 @@ for more details on the API.
Binarization is the process of thresholding numerical features to binary (0/1) features.
-`Binarizer` takes the common parameters `inputCol` and `outputCol`, as well as the `threshold` for binarization. Feature values greater than the threshold are binarized to 1.0; values equal to or less than the threshold are binarized to 0.0.
+`Binarizer` takes the common parameters `inputCol` and `outputCol`, as well as the `threshold`
+for binarization. Feature values greater than the threshold are binarized to 1.0; values equal
+to or less than the threshold are binarized to 0.0. Both Vector and Double types are supported
+for `inputCol`.
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