You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xusen Yin (JIRA)" <ji...@apache.org> on 2015/10/16 05:55:05 UTC
[jira] [Updated] (SPARK-11136) Warm-start support for ML estimator

     [ https://issues.apache.org/jira/browse/SPARK-11136?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xusen Yin updated SPARK-11136:
------------------------------
    Description: 
The current implementation of Estimator does not support warm-start fitting, i.e. estimator.fit(data, params, partialModel). But first we need to add warm-start for all ML estimators. This is an umbrella JIRA to add support for the warm-start estimator. 

Treat model as a special parameter, passing it through ParamMap. e.g. val partialModel: Param[Option[M]] = new Param(...). In the case of model existing, we use it to warm-start, else we start the training process from the beginning.



  was:
The current implementation of Estimator does not support warm-start fitting, i.e. estimator.fit(data, params, partialModel). But first we need to add warm-start for all ML estimators. This is an umbrella JIRA to add support for the warm-start estimator. 

Possible solutions:

1. Add warm-start fitting interface like def fit(dataset: DataFrame, initModel: M, paramMap: ParamMap): M

2. Treat model as a special parameter, passing it through ParamMap. e.g. val partialModel: Param[Option[M]] = new Param(...). In the case of model existing, we use it to warm-start, else we start the training process from the beginning.




> Warm-start support for ML estimator
> -----------------------------------
>
>                 Key: SPARK-11136
>                 URL: https://issues.apache.org/jira/browse/SPARK-11136
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML
>            Reporter: Xusen Yin
>            Priority: Minor
>
> The current implementation of Estimator does not support warm-start fitting, i.e. estimator.fit(data, params, partialModel). But first we need to add warm-start for all ML estimators. This is an umbrella JIRA to add support for the warm-start estimator. 
> Treat model as a special parameter, passing it through ParamMap. e.g. val partialModel: Param[Option[M]] = new Param(...). In the case of model existing, we use it to warm-start, else we start the training process from the beginning.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org