[
https://issues.apache.org/jira/browse/SPARK-16470?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Weichen Xu updated SPARK-16470:
-------------------------------
Description:
In `ml.regression.LinearRegression`, it use breeze `LBFGS` and `OWLQN`
optimizer to do data training, but do not check whether breeze's optimizer
returned result actually reached convergence.
In fact, the `LBFGS` and `OWLQN` optimizer in breeze finish iteration may
result in the following situations:
1) reach max iteration number
2) function reach value convergence
3) objective function stop improving
4) gradient reach convergence
5) search failed(due to some internal numerical error)
only (2) & (4) situations above can be regarded as convergence result.
in other situation, we should at least print some warning to remind spark user.
was:
In `ml.regression.LinearRegression`, it use breeze `LBFGS` and `OWLQN`
optimizer to do data training, but do not check whether breeze's optimizer
returned result actually reached convergence.
In fact, the `LBFGS` and `OWLQN` optimizer in breeze finish iteration may
result the following situations:
1) reach max iteration number
2) function reach value convergence
3) objective function stop improving
4) gradient reach convergence
5) search failed(due to some internal numerical error)
only (2) & (4) situations above can be regarded as convergence result.
in other situation, we should at least print some warning to remind spark user.
> ml.regression.LinearRegression training data do not check whether the result
> actually reach convergence
> -------------------------------------------------------------------------------------------------------
>
> Key: SPARK-16470
> URL: https://issues.apache.org/jira/browse/SPARK-16470
> Project: Spark
> Issue Type: Improvement
> Components: ML, Optimizer
> Affects Versions: 2.0.1, 2.1.0
> Reporter: Weichen Xu
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> In `ml.regression.LinearRegression`, it use breeze `LBFGS` and `OWLQN`
> optimizer to do data training, but do not check whether breeze's optimizer
> returned result actually reached convergence.
> In fact, the `LBFGS` and `OWLQN` optimizer in breeze finish iteration may
> result in the following situations:
> 1) reach max iteration number
> 2) function reach value convergence
> 3) objective function stop improving
> 4) gradient reach convergence
> 5) search failed(due to some internal numerical error)
> only (2) & (4) situations above can be regarded as convergence result.
> in other situation, we should at least print some warning to remind spark
> user.
--
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
