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2010 Book Chapter Clustering of high-dimensional data via finite mixture modelsMcLachlan, Geoff J. and Baek, Jangsun (2010). Clustering of high-dimensional data via finite mixture models. Advances in Data Analysis, Business Intelligence: Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC Helmut-Schmidt-University, Hamburg, July 16–18, 2008. (pp. 33-44) edited by Andreas Fink, Berthold Lausen, Wilfried Seidel and Alfred Ultsch. Heidelberg, Germany: Springer-Verlag. doi: 10.1007/978-3-642-01044-6 |
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2009 Journal Article A score test for assessing the cured proportion in the long-term survivor mixture modelZhao, Yun, Lee, Andy H., Yau, Kelvin K. W., Burke, Valerie and McLachlan, Geoffrey J. (2009). A score test for assessing the cured proportion in the long-term survivor mixture model. Statistics In Medicine, 28 (27), 3454-3466. doi: 10.1002/sim.3696 |
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2009 Conference Publication Ensemble approach for the classification of imbalanced dataNikulin, Vladimir, McLachlan, Geoffrey J. and Ng, Shu Kay (2009). Ensemble approach for the classification of imbalanced data. AI 2009: Advances in Artificial Intelligence, Melbourne, VIC, Australia, 1-4 December 2009. Berlin, Germany: Springer. doi: 10.1007/978-3-642-10439-8_30 |
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2009 Book Chapter Model-based clusteringMcLachlan, G. J. (2009). Model-based clustering. Comprehensive chemometrics: chemical and biochemical data analysis. (pp. 655-681) edited by Steven D. Brown, Roma Tauler and Beata Walczak. Oxford, U.K.: Elsevier Science. doi: 10.1016/B978-044452701-1.00068-5 |
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2009 Book Chapter EMMcLachlan, G. J. and Ng, S-K. (2009). EM. The Top Ten Algorithms in Data Mining. (pp. 93-115) edited by Wu, X. and Kumar, V.. Florida, United States: Chapman & Hall/CRC. doi: 10.1201/9781420089653-12 |
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2009 Journal Article Classification of imbalanced marketing data with balanced random setsNikulin, Vladimir and McLachlan, Geoffrey J. (2009). Classification of imbalanced marketing data with balanced random sets. Journal of Machine Learning Research, 7, 89-100. |
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2009 Conference Publication Multivariate skew t mixture models: applications to fluorescence-activated cell sorting dataWang, Kui, Ng, Shu-Kay and McLachlan, Geoffrey J. (2009). Multivariate skew t mixture models: applications to fluorescence-activated cell sorting data. 2009 Conference of Digital Image Computing: Techniques and Applications, Melbourne, Australia, 1-3 December 2009. Los Alamitos, California: IEEE Computer Society. doi: 10.1109/DICTA.2009.88 |
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2009 Journal Article Automated high-dimensional flow cytometric data analysisPyne, S., Hu, X., Wang, K., Rossin, E., Lin, T.-I., Maier, L. M., Baecher-Allan, C., McLachlan, G. J., Tamayo, P., Hafler, D. A., De Jager, P. L. and Mesirow, J. P. (2009). Automated high-dimensional flow cytometric data analysis. Proceedings of the National Academy of Sciences of the United States of America, 106 (21), 8519-8524. doi: 10.1073/pnas.0903028106 |
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2009 Conference Publication On a general method for matrix factorisation applied to supervised classificationNikulin, Vladimir and McLachlan, Geoffrey J. (2009). On a general method for matrix factorisation applied to supervised classification. 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, Washington, D.C., U.S.A., 1-4 November 2009. Piscataway, NJ, United States: IEEE. doi: 10.1109/BIBMW.2009.5332135 |
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2009 Conference Publication Regularised k-means clustering for dimension reduction applied to supervised classificationNikulin, Vladimir and McLachlan, Geoffrey J. (2009). Regularised k-means clustering for dimension reduction applied to supervised classification. Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics 2009, Genova, Italy, 15-17 October 2009. Salerno, Italy: DMI Proceedings Series. |
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2009 Journal Article Microarray data analysis for differential expression: a tutorialSuarez, E., Burguete, A. and McLachlan, G. J. (2009). Microarray data analysis for differential expression: a tutorial. Puerto Rico Health Sciences Journal, 28 (2), 89-104. |
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2009 Book Chapter Statistical analysis on microarray data: selection of gene prognosis signaturesLe Cao, Kim-Anh and McLachlan, Geoffrey J. (2009). Statistical analysis on microarray data: selection of gene prognosis signatures. Computational biology: issues and applications in oncology. (pp. 55-76) edited by Tuan Pham. New York, United States: Springer. doi: 10.1007/978-1-4419-0811-7_3 |
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2009 Book Chapter Clustering methods for gene-expression dataFlack, L. K. and McLachlan, G. J. (2009). Clustering methods for gene-expression data. Handbook of Research on Systems Biology Applications in Medicine. (pp. 209-220) edited by Andriani Daskalaki. United States: IGI Global. doi: 10.4018/978-1-60566-076-9.ch011 |
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2009 Conference Publication Classification of imbalanced marketing data with balanced random setsNikulin, Vladimir and McLachlan, Geoffrey J. (2009). Classification of imbalanced marketing data with balanced random sets. AISTATS 2009, Clearwater Beach, FL, United States, 16-18 April 2009. Cambridge, MA, United States: M I T Press. |
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2008 Journal Article Wallace's approach to unsupervised learning: The Snob programJorgensen, Murray A. and McLachlan, Geoffrey J. (2008). Wallace's approach to unsupervised learning: The Snob program. The Computer Journal, 51 (5), 571-578. doi: 10.1093/comjnl/bxm121 |
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2008 Journal Article Characteristic Traffic Load Effects from a Mixture of Loading Events on Short to Medium Span BridgesCaprani, C. C., O'Brien, E. J. and McLachlan, G. J. (2008). Characteristic Traffic Load Effects from a Mixture of Loading Events on Short to Medium Span Bridges. Structural Safety, 30 (3), 394-404. doi: 10.1016/j.strusafe.2006.11.006 |
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2008 Book Chapter Clustering of microarray data via mixture modelsMcLachlan, Geoffrey J., Ng, Angus and Bean, Richard W. (2008). Clustering of microarray data via mixture models. Statistical advances in the biomedical sciences: clinical trials, epidemiology, survival analysis, and bioinformatics. (pp. 365-383) edited by Atanu Biswas, Sujay Datta, Jason P. Fine and Mark R. Segal. Hoboken, NJ, United States: John Wiley & Sons. doi: 10.1002/9780470181218.ch21 |
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2008 Journal Article Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) StudyMcLaren, C. E., Gordeuk, V. R., Chen, W. -P., Barton, J. C., Action, R. T., Speechley, M., Castro, O., Adams, P. C., Snively, B. M., Harris, E. L., Reboussin, D. M., McLachlan, G. J. and Bean, R. (2008). Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. Translational Research, 151 (2), 97-109. doi: 10.1016/j.trsl.2007.10.002 |
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2008 Journal Article On selection biases with prediction rules formed from gene expression dataZhu, J. X., McLachlan, G. J., Jones, L. B. T. and Wood, I. A. (2008). On selection biases with prediction rules formed from gene expression data. Journal of Statistical Planning and Inference, 138 (2), 374-386. doi: 10.1016/j.jspi.2007.06.003 |
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2008 Journal Article Comments on: Augmenting the bootstrap to analyze high dimensional genomic dataMcLachlan, Geoffrey J., Wang, K. and Ng, S. K. (2008). Comments on: Augmenting the bootstrap to analyze high dimensional genomic data. Test, 17 (1), 43-46. doi: 10.1007/s11749-008-0106-x |
