Barry Becker created SPARK-17086:
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Summary: QuantileDiscretizer throws InvalidArgumentException
(parameter splits given invalid value) on valid data
Key: SPARK-17086
URL: https://issues.apache.org/jira/browse/SPARK-17086
Project: Spark
Issue Type: Bug
Components: ML
Affects Versions: 2.1.0
Reporter: Barry Becker
I discovered this bug when working with a build from the master branch (which I
believe is 2.1.0). This used to work fine when running spark 1.6.2.
I have a dataframe with an "intData" column that has values like
{code}
1 3 2 1 1 2 3 2 2 2 1 3
{code}
I have a stage in my pipeline that uses the QuantileDiscretizer to produce
equal weight splits like this
{code}
new QuantileDiscretizer()
.setInputCol("intData")
.setOutputCol("intData_bin")
.setNumBuckets(10)
.fit(df)
{code}
But when that gets run it (incorrectly) throws this error:
{code}
parameter splits given invalid value [-Infinity, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0,
Infinity]
{code}
I don't think that there should be duplicate splits generated should there be?
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