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https://issues.apache.org/jira/browse/SPARK-12732?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-12732:
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Assignee: Apache Spark
> Fix LinearRegression.train for the case when label is constant and
> fitIntercept=false
> -------------------------------------------------------------------------------------
>
> Key: SPARK-12732
> URL: https://issues.apache.org/jira/browse/SPARK-12732
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Reporter: Imran Younus
> Assignee: Apache Spark
> Priority: Minor
>
> If the target variable is constant, then the linear regression must check if
> the fitIntercept is true or false, and handle these two cases separately.
> If the fitIntercept is true, then there is no training needed and we set the
> intercept equal to the mean of y.
> But if the fit intercept is false, then the model should still train.
> Currently, LinearRegression handles both cases in the same way. It doesn't
> train the model and sets the intercept equal to the mean of y. Which, means
> that it returns a non-zero intercept even when the user forces the regression
> through the origin.
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