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https://issues.apache.org/jira/browse/MATH-1371?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15307029#comment-15307029
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Artem Barger commented on MATH-1371:
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Ok, got it.
I'd prefer to first finish w/ current ticket first.
So just to make it clear and to get the scope of the changes I need to provide
in order to
make this implementation accepted:
1. Replace JDKRandomGenerator.
2. Add unit tests.
3. Convert instance variables into local.
Anything else?
PS. Do I need actually to keep calling it ElkanKmeansPlusPlusClusterer?
> Provide accelerated kmeans++ implementation
> -------------------------------------------
>
> Key: MATH-1371
> URL: https://issues.apache.org/jira/browse/MATH-1371
> Project: Commons Math
> Issue Type: Improvement
> Reporter: Artem Barger
> Assignee: Artem Barger
> Attachments: ElkanKmeansPlusPlusClusterer.java
>
>
> There is an updated version of kmeans++ algorithm available, which is
> published in: Elkan, Charles. "Using the triangle inequality to accelerate
> k-means." ICML. Vol. 3. 2003. paper.
> The main essence is to boost the kmeans iterations by avoiding computation of
> distances between centers and points when there is no need for that. For
> example after the update cluster center haven't moved too far from the point
> therefore no change in point assignment. The accelerated algorithm avoids
> unnecessary distance calculations by applying the triangle inequality in two
> different ways, and by keeping track of lower and upper bounds for distances
> between points and centers.
> Algorithm description is available in the paper.
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