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https://issues.apache.org/jira/browse/SPARK-2552?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14067419#comment-14067419
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Xiangrui Meng commented on SPARK-2552:
--------------------------------------
It is not necessary to check the ranges because exp never underflows on a
negative number. So the function is just
{code}
def logistic(x):
if x > 0:
return 1 / (1 + math.exp(-x))
else
return 1 - 1 / (1 + math.exp(x))
{code}
> Stabilize the computation of logistic function in pyspark
> ---------------------------------------------------------
>
> Key: SPARK-2552
> URL: https://issues.apache.org/jira/browse/SPARK-2552
> Project: Spark
> Issue Type: Bug
> Components: MLlib, PySpark
> Reporter: Xiangrui Meng
> Labels: Starter
>
> exp(1000) throws an error in python. For logistic function, we can use either
> 1 / ( 1 + exp( -x ) ) or 1 - 1 / (1 + exp( x ) ) to compute its value which
> ensuring exp always takes a negative value.
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