ORKM: An R package for online multi-view data clustering

We propose a package called ORKM, which implements the ORKMC (Online Regularized K-Means Clustering) method for handling online multi-view or single-view data, which named ORKMeans function in the package incorporates a regularization term to address multi-view clustering problems with online update...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) Vol. 663; p. 131973
Main Authors: Yu, Miao, Li, Shu, Guo, Guangbao
Format: Journal Article
Language:English
Published: Elsevier B.V 28.01.2026
Elsevier
Subjects:
Computer Science
Data Structures and Algorithms
Online K-means clustering
Online multi-view data
Regularization
Single-view
Online K-means clustering
Single-view
Online multi-view data
Regularization
ISSN:0925-2312
Online Access:Get full text
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Summary:We propose a package called ORKM, which implements the ORKMC (Online Regularized K-Means Clustering) method for handling online multi-view or single-view data, which named ORKMeans function in the package incorporates a regularization term to address multi-view clustering problems with online updates. ORKM computes classification results, cluster center matrices, and view-specific weights for multi-view datasets. It also supports branching multi/single-view data by converting the online RKMC algorithm into an offline version, referred to as RKMC (Regularized K-Means Clustering) realized by function RKMeans. We demonstrate the package’s functionality through simulations and real-world data analyses, comparing it with other methods and related R packages. Overall, ORKM exhibits stable performance and effective clustering results.
ISSN:0925-2312
DOI:10.1016/j.neucom.2025.131973