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https://issues.apache.org/jira/browse/SPARK-21818?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-21818.
-------------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
Issue resolved by pull request 19029
[https://github.com/apache/spark/pull/19029]
> MultivariateOnlineSummarizer.variance generate negative result
> --------------------------------------------------------------
>
> Key: SPARK-21818
> URL: https://issues.apache.org/jira/browse/SPARK-21818
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib
> Affects Versions: 2.2.0
> Reporter: Weichen Xu
> Fix For: 2.3.0
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Because of numerical error, MultivariateOnlineSummarizer.variance is possible
> to generate negative variance.
> This is a serious bug because many algos in MLLib use stddev computed from
> sqrt(variance),
> it will generate NaN and crash the whole algorithm.
> we can reproduce this bug use the following code:
> {code}
> val summarizer1 = (new MultivariateOnlineSummarizer)
> .add(Vectors.dense(3.0), 0.7)
> val summarizer2 = (new MultivariateOnlineSummarizer)
> .add(Vectors.dense(3.0), 0.4)
> val summarizer3 = (new MultivariateOnlineSummarizer)
> .add(Vectors.dense(3.0), 0.5)
> val summarizer4 = (new MultivariateOnlineSummarizer)
> .add(Vectors.dense(3.0), 0.4)
> val summarizer = summarizer1
> .merge(summarizer2)
> .merge(summarizer3)
> .merge(summarizer4)
> println(summarizer.variance(0))
> {code}
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