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From "Sachin Goel (JIRA)" <j...@apache.org>
Subject [jira] [Created] (FLINK-2131) Add Initialization schemes for K-means clustering
Date Tue, 02 Jun 2015 02:18:17 GMT
Sachin Goel created FLINK-2131:

             Summary: Add Initialization schemes for K-means clustering
                 Key: FLINK-2131
                 URL: https://issues.apache.org/jira/browse/FLINK-2131
             Project: Flink
          Issue Type: Task
          Components: Machine Learning Library
            Reporter: Sachin Goel
            Assignee: Sachin Goel

The Lloyd's [KMeans] algorithm takes initial centroids as its input. However, in case the
user doesn't provide the initial centers, they may ask for a particular initialization scheme
to be followed. The most commonly used are these:
1. Random initialization: Self-explanatory
2. kmeans++ initialization: http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
3. kmeans|| : http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf

For very large data sets, or for large values of k, the kmeans|| method is preferred as it
provides the same approximation guarantees as kmeans++ and requires lesser number of passes
over the input data.

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