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  1. Apache MADlib
  2. MADLIB-1059

Add additional distance metrics for k-NN

    Details

    • Type: Improvement
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: v1.13
    • Component/s: k-NN
    • Labels:

      Description

      Follow on from https://issues.apache.org/jira/browse/MADLIB-927
      which supports one distance function. This JIRA is to

      (1)
      add additional distance metrics. The model is follow is
      http://madlib.incubator.apache.org/docs/latest/group__grp__kmeans.html

      fn_dist (optional)
      TEXT, default: squared_dist_norm2'. The name of the function to use to calculate the distance between data points.

      The following distance functions can be used (computation of barycenter/mean in parentheses):

      dist_norm1: 1-norm/Manhattan (element-wise median [Note that MADlib does not provide a median aggregate function for support and performance reasons.])
      dist_norm2: 2-norm/Euclidean (element-wise mean)
      squared_dist_norm2: squared Euclidean distance (element-wise mean)
      dist_angle: angle (element-wise mean of normalized points)
      dist_tanimoto: tanimoto (element-wise mean of normalized points [5])
      user defined function with signature DOUBLE PRECISION[] x, DOUBLE PRECISION[] y -> DOUBLE PRECISION

      and also check of there are other distance functions under
      http://madlib.apache.org/docs/latest/group__grp__linalg.html
      that might make sense to include while you are at it, in addition to the ones listed above

      (2) Add an option for weighted average in the voting.

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              • Assignee:
                riyer Rahul Iyer
                Reporter:
                fmcquillan Frank McQuillan
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                • Created:
                  Updated:
                  Resolved: