[jira] [Commented] (SPARK-4588) Add API for feature attributes

2015-03-05 Thread Apache Spark (JIRA)

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https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14349907#comment-14349907
 ] 

Apache Spark commented on SPARK-4588:
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User 'mengxr' has created a pull request for this issue:
https://github.com/apache/spark/pull/4925

 Add API for feature attributes
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 Key: SPARK-4588
 URL: https://issues.apache.org/jira/browse/SPARK-4588
 Project: Spark
  Issue Type: Sub-task
  Components: ML, MLlib
Reporter: Xiangrui Meng
Assignee: Sean Owen
Priority: Critical

 Feature attributes, e.g., continuous/categorical, feature names, feature 
 dimension, number of categories, number of nonzeros (support) could be useful 
 for ML algorithms.
 In SPARK-3569, we added metadata to schema, which can be used to store 
 feature attributes along with the dataset. We need to provide a wrapper over 
 the Metadata class for ML usage.
 The design doc is available at 
 https://docs.google.com/document/d/1796XfSzFbZvGWFs0ky99AJhlqkOBRG1O2bUxK2N4Grk/edit?usp=sharing



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[jira] [Commented] (SPARK-4588) Add API for feature attributes

2015-02-08 Thread Apache Spark (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14311586#comment-14311586
 ] 

Apache Spark commented on SPARK-4588:
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User 'srowen' has created a pull request for this issue:
https://github.com/apache/spark/pull/4460

 Add API for feature attributes
 --

 Key: SPARK-4588
 URL: https://issues.apache.org/jira/browse/SPARK-4588
 Project: Spark
  Issue Type: Sub-task
  Components: ML, MLlib
Reporter: Xiangrui Meng
Assignee: Sean Owen

 Feature attributes, e.g., continuous/categorical, feature names, feature 
 dimension, number of categories, number of nonzeros (support) could be useful 
 for ML algorithms.
 In SPARK-3569, we added metadata to schema, which can be used to store 
 feature attributes along with the dataset. We need to provide a wrapper over 
 the Metadata class for ML usage.



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