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  1. Spark
  2. SPARK-2335

k-Nearest Neighbor classification and regression for MLLib

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    Details

    • Type: New Feature
    • Status: Resolved
    • Priority: Minor
    • Resolution: Duplicate
    • Affects Version/s: None
    • Fix Version/s: None
    • Component/s: MLlib

      Description

      The k-Nearest Neighbor model for classification and regression problems is a simple and intuitive approach, offering a straightforward path to creating non-linear decision/estimation contours. It's downsides – high variance (sensitivity to the known training data set) and computational intensity for estimating new point labels – both play to Spark's big data strengths: lots of data mitigates data concerns; lots of workers mitigate computational latency.

      We should include kNN models as options in MLLib.

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              • Assignee:
                Unassigned
                Reporter:
                bgawalt Brian Gawalt
                Shepherd:
                Ashutosh Trivedi
              • Votes:
                5 Vote for this issue
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                26 Start watching this issue

                Dates

                • Created:
                  Updated:
                  Resolved: