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Multiple alternative clusterings and dimensionality reduction: Theory and application

Multiple alternative clusterings and dimensionality reduction: Theory and application

Authors
Publisher Scholar's Press
Year
Pages 148
Version paperback
Language English
ISBN 9783639718867
Categories
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Book description

Clustering is the process of grouping objects based on some notion of similarity. It is commonly applied for exploratory data analysis, segmentation, preprocessing and data summarization.Traditional clustering algorithms only find one clustering solution. However, data can be grouped and interpreted in many different ways. Moreover, different clustering solutions are interesting for different purposes. Instead of committing to one clustering solution, here we introduce four methods that can provide several possible alternative clustering solutions to the user for exploratory data analysis.

Multiple alternative clusterings and dimensionality reduction: Theory and application

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