[
https://issues.apache.org/jira/browse/SPARK-13777?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-13777:
------------------------------------
Assignee: (was: Apache Spark)
> Weighted Leaset Squares fails when there are features with identical values.
> ----------------------------------------------------------------------------
>
> Key: SPARK-13777
> URL: https://issues.apache.org/jira/browse/SPARK-13777
> Project: Spark
> Issue Type: Bug
> Components: ML
> Reporter: Imran Younus
> Priority: Minor
>
> "normal" solver in LinearRegression uses Cholesky decomposition to calculate
> the coefficients. If the data has features with identical values (zero
> variance), then (A^T A) matrix is not positive definite any more and the
> Cholesky decomposition fails.
> For the same case, "l-bfgs" solver sets the coefficients of these constant
> features to zero and produces valid coefficients for the rest of the
> features. This behaviour is consistent with glmnet in R. "normal" solver
> should also do the same.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
