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Diffstat (limited to 'python/pyspark/ml/feature.py')
| -rwxr-xr-x | python/pyspark/ml/feature.py | 5 |
1 files changed, 5 insertions, 0 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 2881380152..c45434f1a5 100755 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -1155,6 +1155,11 @@ class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadab `QuantileDiscretizer` takes a column with continuous features and outputs a column with binned categorical features. The number of bins can be set using the :py:attr:`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). The bin ranges are chosen using an approximate algorithm (see the documentation for :py:meth:`~.DataFrameStatFunctions.approxQuantile` for a detailed description). The precision of the approximation can be controlled with the |