[ https://issues.apache.org/jira/browse/SPARK-5114?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-5114: ------------------------------------- Description: Pipelines can currently contain Estimators and Transformers. Question for debate: Should Pipelines be able to contain Evaluators? Pros: * Schema check: Evaluators take input datasets with particular schema, which should perhaps be checked before running a Pipeline. * Intermediate results: ** If a Transformer removes a column (which is not done by built-in Transformers currently but might be reasonable in the future), then the user can never evaluate that column. (However, users could keep all columns around.) ** If users have to evaluate after running a Pipeline, then each evaluated column may have to be re-materialized. Cons: * API: Evaluators do not transform datasets. They produce a scalar (or a few values), which makes it hard to say how they fit into a Pipeline or a PipelineModel. was: Pipelines can currently contain Estimators and Transformers. Question for debate: Should Pipelines be able to contain Evaluators? Pros: * Schema check: Evaluators take input datasets with particular schema, which should perhaps be checked before running a Pipeline. * Intermediate results: ** If a Transformer removes a column (which is not done by built-in Transformers currently but might be reasonable in the future), then the user can never evaluate that column. (However, users could keep all columns around.) ** If users have to evaluate after running a Pipeline, then each evaluated column may have to be re-materialized. Cons: * Evaluators do not transform datasets. They produce a scalar (or a few values), which makes it hard to say how they fit into a Pipeline or a PipelineModel. > Should Evaluator be a PipelineStage > ----------------------------------- > > Key: SPARK-5114 > URL: https://issues.apache.org/jira/browse/SPARK-5114 > Project: Spark > Issue Type: Question > Components: ML > Affects Versions: 1.2.0 > Reporter: Joseph K. Bradley > > Pipelines can currently contain Estimators and Transformers. > Question for debate: Should Pipelines be able to contain Evaluators? > Pros: > * Schema check: Evaluators take input datasets with particular schema, which > should perhaps be checked before running a Pipeline. > * Intermediate results: > ** If a Transformer removes a column (which is not done by built-in > Transformers currently but might be reasonable in the future), then the user > can never evaluate that column. (However, users could keep all columns > around.) > ** If users have to evaluate after running a Pipeline, then each evaluated > column may have to be re-materialized. > Cons: > * API: Evaluators do not transform datasets. They produce a scalar (or a > few values), which makes it hard to say how they fit into a Pipeline or a > PipelineModel. -- 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