Weighted Mutual Information for Aggregated Kernel Clustering

<b>Background:</b> A common task in machine learning is clustering data into different groups based on similarities. Clustering methods can be divided in two groups: linear and nonlinear. A commonly used linear clustering method is K-means. Its extension, kernel K-means, is a non-linear...

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Auteurs principaux: Nezamoddin N. Kachouie, Meshal Shutaywi
Format: Artigo
Langue:Inglês
Publié: MDPI AG 2020-03-01
Collection:Entropy
Sujets:
weighted mutual information
aggregated clustering
kernel k-means
conditional entropy
Accès en ligne:https://www.mdpi.com/1099-4300/22/3/351
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