[
https://issues.apache.org/jira/browse/SPARK-30210?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17252664#comment-17252664
]
Nicholas Brett Marcott commented on SPARK-30210:
------------------------------------------------
[~anzelpwj] could you provide a simple code example to reproduce the error?
My simple case (a few others attempted as well) which only reference one label
doesn't throw errors:
{code:java}
>>> from pyspark.ml.evaluation import BinaryClassificationEvaluator
>>> evaluator = BinaryClassificationEvaluator(labelCol='label',
>>> metricName='areaUnderROC')
>>> df = spark.createDataFrame([(1.0,1.0)],['label','rawPrediction'])
>>> evaluator.evaluate(df)
1.0
{code}
> Give more informative error for BinaryClassificationEvaluator when data with
> only one label is provided
> -------------------------------------------------------------------------------------------------------
>
> Key: SPARK-30210
> URL: https://issues.apache.org/jira/browse/SPARK-30210
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.1.0
> Environment: Pyspark on Databricks
> Reporter: Paul Anzel
> Priority: Minor
>
> Hi all,
> When I was trying to do some machine learning work with pyspark I ran into a
> confusing error message:
> {{# Model and train/test set generated...}}
> {{ evaluator = BinaryClassificationEvaluator(labelCol=label,
> metricName='areaUnderROC')}}
> {{ prediction = model.transform(test_data)}}
> {{ auc = evaluator.evaluate(prediction)}}
> {{org.apache.spark.SparkException: Job aborted due to stage failure: Task 37
> in stage 21.0 failed 4 times, most recent failure: Lost task 37.3 in stage
> 21.0 (TID 2811, 10.139.65.48, executor 16):
> java.lang.ArrayIndexOutOfBoundsException}}
> After some investigation, I found that the issue was that the data I was
> trying to predict on only had one label represented, rather than both
> positive and negative labels. Easy enough to fix, but I would like to ask if
> we could replace this error with one that explicitly points out the issue.
> Would it be acceptable to have a check ahead of time on labels that ensures
> all labels are represented? Alternately, can we change the docs for
> BinaryClassificationEvaluator to explain what this error means?
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
