Multiple alternative clusterings and dimensionality reduction: Theory and application - Couverture souple

Niu, Donglin

 
9783639718867: Multiple alternative clusterings and dimensionality reduction: Theory and application

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.