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Posted to issues@flink.apache.org by "Sachin Goel (JIRA)" <ji...@apache.org> on 2015/06/02 04:18:17 UTC
[jira] [Created] (FLINK-2131) Add Initialization schemes for
K-means clustering
Sachin Goel created FLINK-2131:
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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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