[ https://issues.apache.org/jira/browse/MADLIB-1059?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Frank McQuillan updated MADLIB-1059: ------------------------------------ Fix Version/s: (was: v2.0) v1.13 > Add additional distance metrics for k-NN > ---------------------------------------- > > Key: MADLIB-1059 > URL: https://issues.apache.org/jira/browse/MADLIB-1059 > Project: Apache MADlib > Issue Type: Improvement > Components: k-NN > Reporter: Frank McQuillan > Assignee: Himanshu Pandey > Labels: starter > Fix For: v1.13 > > > 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 message was sent by Atlassian JIRA (v6.4.14#64029)