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

2015-03-04 Thread Xiangrui Meng (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiangrui Meng updated SPARK-4588:
-
Description: 
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

  was:
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.


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

2015-02-16 Thread Xiangrui Meng (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiangrui Meng updated SPARK-4588:
-
Priority: Critical  (was: Major)

 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
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.



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

2015-02-02 Thread Xiangrui Meng (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiangrui Meng updated SPARK-4588:
-
Target Version/s: 1.4.0  (was: 1.3.0)

 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

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

2015-02-02 Thread Xiangrui Meng (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-4588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiangrui Meng updated SPARK-4588:
-
Assignee: Sean Owen

 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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