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Journeys to Data Mining pp 147–171Cite as

An Enduring Interest in Classification: Supervised and Unsupervised

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Abstract

I have researched in the field of discriminant analysis for over 40 years and for nearly as long in the field of cluster analysis. Thus, I think it is fair to say that I have had an enduring interest in discriminant and cluster analyses, that is, in classification both supervised and unsupervised. The latter terminology is used outside of statistics in fields such as artificial intelligence, machine learning, and pattern recognition. However, the gap between these fields and statistics has narrowed appreciably over the years, and discriminant analysis and cluster analysis are also often referred in statistics as supervised classification and unsupervised classification, respectively.

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Acknowledgements

The work for this chapter was supported by a grant from the Australian Research Council.

I would like to thank my collaborators on various aspects of my research relevant to data mining over the years, including Peter Adams, Christophe Ambroise, Jangsun Baek, Kaye Basford, Richard Bean, Liat Ben-Tovim Jones, Karen Byth, Igor Cadez, Kim-Anh Le Cao, Soong Chang, Jonathan Chevelu, Kim-Anh Do, Lloyd Flack, S. Ganesalingam, Doug Hawkins, Tian-Hsiang Huang, Peter Jones, Murray Jorgensen, Nazim Khan, Thriyambakam Krishnan, Charles Lawoko, Andy Lee, Jess Mar, Camille Maumet, Christine McLaren, Emmanuelle Meugnier, Katrina Monico, Angus Ng, Vladimir Nikulin, David Peel, Saumyadipta Pyne, Barry Quinn, Suren Rathnayake, Mohamed Shoukri, Padhraic Smyth, Erick Suarez, Deming Wang, Kui (Sam) Wang, Bill Whiten, Leesa Wockner, Ian Wood, Kelvin Yau, and Justin Zhu.

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    G. J. McLachlan

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    Mohamed Medhat Gaber

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McLachlan, G.J. (2012). An Enduring Interest in Classification: Supervised and Unsupervised. In: Gaber, M. (eds) Journeys to Data Mining. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28047-4_12

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