A Low Dimensional Embedding Method for Combining Clusterings

Sen Xu; Tian Zhou; Hua Long Yu

doi:10.4028/www.scientific.net/AMR.201-203.2517

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 201-203A Low Dimensional Embedding Method for Combining...

A Low Dimensional Embedding Method for Combining Clusterings

Abstract:

Clustering combination has recently become a hotspot in machine learning, while its critical problem lies on how to combine multiple clusterings to yield a final superior result. In this paper, a low dimensional embedding method is proposed. It first obtains the low dimensional embeddings of hyperedges by performing spectral clustering algorithms and then obtains the low dimensional embeddings of objects indirectly by composition of mappings and finally performs K-means algorithm to cluster the objects according to their coordinates in the low dimensional space. Experimentally the proposed method is shown to perform well.

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Advanced Manufacturing Systems, ICMSE 2011

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Periodical:

Advanced Materials Research (Volumes 201-203)

Pages:

2517-2520

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.201-203.2517

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Online since:

February 2011

Authors:

Sen Xu, Tian Zhou, Hua Long Yu

Keywords:

Clustering, Clustering Combination, Low Dimensional Embedding, Machine Learning (ML)

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