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https://issues.apache.org/jira/browse/MAHOUT-209?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jake Mannix reassigned MAHOUT-209:
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Assignee: Jake Mannix
> Add aggregate() methods for Vector
> ----------------------------------
>
> Key: MAHOUT-209
> URL: https://issues.apache.org/jira/browse/MAHOUT-209
> Project: Mahout
> Issue Type: Improvement
> Components: Matrix
> Environment: all
> Reporter: Jake Mannix
> Assignee: Jake Mannix
> Priority: Minor
> Fix For: 0.3
>
>
> As discussed in MAHOUT-165 at some point, Vector (and Matrix, but let's put
> that on a separate ticket) could do with a nice exposure of methods like the
> following:
> {code}
> // this can get optimized, of course
> public double aggregate(Vector other, BinaryFunction aggregator,
> BinaryFunction combiner) {
> double result = 0;
> for(int i=0; i<size(); i++) {
> result = aggregator.apply(result, combiner.apply(getQuick(i),
> other.getQuick(i)));
> }
> return result;
> }
> {code}
> this is good for generalized inner products and distances. Also nice:
> {code}
> public double aggregate(BinaryFunction aggregator, UnaryFunction map) {
> double result = 0;
> for(int i=0; i<size(); i++) {
> result = aggregator.apply(result, map.apply(getQuick(i)) );
> }
> return result;
> }
> {code}
> Which generalizes norms and statistics (mean, median, stdDev) and things like
> that (number of positive values, or negative values, etc...).
> These kind of thing exists in Colt, and we could just surface it up to the
> top.
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