Abstract
We develop a consensus clustering framework proposed three decades ago in Russia and experimentally demonstrate that our least squares consensus clustering algorithm consistently outperforms several recent consensus clustering methods.
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Acknowledgements
This work was supported by the research grant “Methods for the analysis and visualization of texts” No. 13-05-0047 under The National Research University Higher School of Economics Academic Fund Program in 2013.
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Mirkin, B., Shestakov, A. (2014). A Note on the Effectiveness of the Least Squares Consensus Clustering. In: Aleskerov, F., Goldengorin, B., Pardalos, P. (eds) Clusters, Orders, and Trees: Methods and Applications. Springer Optimization and Its Applications, vol 92. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0742-7_11
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DOI: https://doi.org/10.1007/978-1-4939-0742-7_11
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