[jira] [Created] (SPARK-11136) Warm-start support for ML estimator

["Xusen Yin (JIRA)" <ji...@apache.org>]

Xusen Yin created SPARK-11136:
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             Summary: 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. 

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.





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