spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Yu Ishikawa (JIRA)" <>
Subject [jira] [Updated] (SPARK-2429) Hierarchical Implementation of KMeans
Date Wed, 29 Oct 2014 13:16:33 GMT


Yu Ishikawa updated SPARK-2429:
    Attachment: benchmark-result.2014-10-29.html

I added a new performance test results named `benchmark-result.2014-10-29.html`.  The main
change from the previous result is that I added the benchmark result about vector sparsity.
Please check it.

> Hierarchical Implementation of KMeans
> -------------------------------------
>                 Key: SPARK-2429
>                 URL:
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: RJ Nowling
>            Assignee: Yu Ishikawa
>            Priority: Minor
>         Attachments: 2014-10-20_divisive-hierarchical-clustering.pdf, The Result of Benchmarking
a Hierarchical Clustering.pdf, benchmark-result.2014-10-29.html, benchmark2.html
> Hierarchical clustering algorithms are widely used and would make a nice addition to
MLlib.  Clustering algorithms are useful for determining relationships between clusters as
well as offering faster assignment. Discussion on the dev list suggested the following possible
> * Top down, recursive application of KMeans
> * Reuse DecisionTree implementation with different objective function
> * Hierarchical SVD
> It was also suggested that support for distance metrics other than Euclidean such as
negative dot or cosine are necessary.

This message was sent by Atlassian JIRA

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message