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Joseph K. Bradley commented on SPARK-11136: ------------------------------------------- We should definitely have it be a Param. I just comment on the KMeans JIRA about that. Thanks for pointing out that issue. Would you mind updating this JIRA's description to specify that as the chosen option? > 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. -- 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