Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/15428#discussion_r83911282 --- Diff: docs/ml-features.md --- @@ -1104,9 +1104,11 @@ for more details on the API. `QuantileDiscretizer` takes a column with continuous features and outputs a column with binned categorical features. The number of bins is set by the `numBuckets` parameter. It is possible that the number of buckets used will be less than this value, for example, if there are too few -distinct values of the input to create enough distinct quantiles. Note also that NaN values are -handled specially and placed into their own bucket. For example, if 4 buckets are used, then -non-NaN data will be put into buckets[0-3], but NaNs will be counted in a special bucket[4]. +distinct values of the input to create enough distinct quantiles. Note also that QuantileDiscretizer --- End diff -- (same as below) Is "possible that the number of buckets used will be less than this value" true? It was true before this used Dataset.approxQuantiles, but I don't think it is true any longer.
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