spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Meihua Wu (JIRA)" <>
Subject [jira] [Commented] (SPARK-7129) Add generic boosting algorithm to
Date Mon, 05 Oct 2015 06:36:26 GMT


Meihua Wu commented on SPARK-7129:

Currently I am not aware of a straightforward way to impose the weak restriction using the
type system yet. Let's keep discuss. 

> Add generic boosting algorithm to
> ------------------------------------------
>                 Key: SPARK-7129
>                 URL:
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: Joseph K. Bradley
> The Pipelines API will make it easier to create a generic Boosting algorithm which can
work with any Classifier or Regressor. Creating this feature will require researching the
possible variants and extensions of boosting which we may want to support now and/or in the
future, and planning an API which will be properly extensible.
> In particular, it will be important to think about supporting:
> * multiple loss functions (for AdaBoost, LogitBoost, gradient boosting, etc.)
> * multiclass variants
> * multilabel variants (which will probably be in a separate class and JIRA)
> * For more esoteric variants, we should consider them but not design too much around
them: totally corrective boosting, cascaded models
> Note: This may interact some with the existing tree ensemble methods, but it should be
largely separate since the tree ensemble APIs and implementations are specialized for trees.

This message was sent by Atlassian JIRA

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message