[jira] [Commented] (SPARK-8518) Log-linear models for survival analysis

["Yanbo Liang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-8518?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14679918#comment-14679918 ] 

Yanbo Liang commented on SPARK-8518:
------------------------------------

[~mengxr] [~meihuawu]
I have update the design document, please review and comment it.
For the questions I can also clarify here:
1. Which algorithm is the most popular one?
Accelerated Failure Time (AFT) model
2. What is the size of the model?
It contains a weight vector (with intercept) and a scale parameter.
3. How do the algorithms fit into Spark? Are they easy to be parallelized?
I have got the loss function and gradient function, so we can parallelize it using SGD or L-BFGS.
4. What is the complexity?
It has the same complexity with LinearRegression.

> Log-linear models for survival analysis
> ---------------------------------------
>
>                 Key: SPARK-8518
>                 URL: https://issues.apache.org/jira/browse/SPARK-8518
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: Xiangrui Meng
>            Assignee: Yanbo Liang
>   Original Estimate: 168h
>  Remaining Estimate: 168h
>
> We want to add basic log-linear models for survival analysis. The implementation should match the result from R's survival package (http://cran.r-project.org/web/packages/survival/index.html).
> Design doc from [~yanboliang]: https://docs.google.com/document/d/1fLtB0sqg2HlfqdrJlNHPhpfXO0Zb2_avZrxiVoPEs0E/pub



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