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  1. Spark
  2. SPARK-5272

Refactor NaiveBayes to support discrete and continuous labels,features

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    Details

    • Type: Improvement
    • Status: Resolved
    • Priority: Major
    • Resolution: Incomplete
    • Affects Version/s: 1.2.0
    • Fix Version/s: None
    • Component/s: MLlib

      Description

      This JIRA is to discuss refactoring NaiveBayes in order to support both discrete and continuous labels and features.

      Currently, NaiveBayes supports only discrete labels and features.

      Proposal: Generalize it to support continuous values as well.

      Some items to discuss are:

      • How commonly are continuous labels/features used in practice? (Is this necessary?)
      • What should the API look like?
        • E.g., should NB have multiple classes for each type of label/feature, or should it take a general Factor type parameter?

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              • Assignee:
                Unassigned
                Reporter:
                josephkb Joseph K. Bradley
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                • Created:
                  Updated:
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