Major 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.
- this requirement moved to a separate JIRA: https://issues.apache.org/jira/browse/MADLIB-1181
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