Geoffrey J. McLachlan

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2011
50Mixtures of common t-factor analyzers for clustering high-dimensional microarray data. Jangsun Baek, Geoffrey J. McLachlan. Bioinformatics (27): 1269-1276 (2011). Web SearchBibTeXDownload
49Classification of High-Dimensional microarray Data with a Two-Step Procedure via a Wilcoxon Criterion and Multilayer Perceptron. Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan. International Journal of Computational Intelligence and Applications (10): 1-14 (2011). Web SearchBibTeXDownload
2010
48A comparative study of two matrix factorization methods applied to the classification of gene expression data. Vladimir Nikulin, Tian-Hsiang Huang, Geoffrey J. McLachlan. BIBM 2010, 618-621. Web SearchBibTeXDownload
47Integrative mixture of experts to combine clinical factors and gene markers. Kim-Anh Lê Cao, Emmanuelle Meugnier, Geoffrey J. McLachlan. Bioinformatics (26): 1192-1198 (2010). Web SearchBibTeXDownload
46On the Gradient-based Algorithm for Matrix Factorization Applied to Dimensionality Reduction. Vladimir Nikulin, Geoffrey J. McLachlan. BIOINFORMATICS 2010, 147-152. Web SearchBibTeX
45A Very Fast Algorithm for Matrix Factorization. Vladimir Nikulin, Tian-Hsiang Huang, Shu-Kay Ng, Suren I Rathnayake, Geoffrey J. McLachlan. CoRR (abs/1011.0506) (2010). Web SearchBibTeXDownload
44Assessing the Significance of Groups in High-Dimensional Data. Geoffrey J. McLachlan. ICDM 2010, 6. Web SearchBibTeXDownload
43Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data. Jangsun Baek, Geoffrey J. McLachlan, Lloyd K. Flack. IEEE Trans. Pattern Anal. Mach. Intell. (32): 1298-1309 (2010). Web SearchBibTeXDownload
42Automated High-Dimensional Flow Cytometric Data Analysis. Saumyadipta Pyne, Xinli Hu, Kui Wang, Elizabeth Rossin, Tsung I. Lin, Lisa Maier, Clare Baecher-Allan, Geoffrey J. McLachlan, Pablo Tamayo, David Hafler, Philip L. De Jager, Jill P. Mesirov. RECOMB 2010, 577. Web SearchBibTeXDownload
2009
41Ensemble Approach for the Classification of Imbalanced Data. Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay Ng. Australasian Conference on Artificial Intelligence 2009, 291-300. Web SearchBibTeXDownload
40Penalized Principal Component Analysis of Microarray Data. Vladimir Nikulin, Geoffrey J. McLachlan. CIBB 2009, 82-96. Web SearchBibTeXDownload
39Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data. Kui Wang, Shu-Kay Ng, Geoffrey J. McLachlan. DICTA 2009, 526-531. Web SearchBibTeXDownload
38Classification of Imbalanced Marketing Data with Balanced Random Sets. Vladimir Nikulin, Geoffrey J. McLachlan. Journal of Machine Learning Research - Proceedings Track (7): 89-100 (2009). Web SearchBibTeXDownload
2008
37Wallace's Approach to Unsupervised Learning: The Snob Program. Murray A. Jorgensen, Geoffrey J. McLachlan. Comput. J. (51): 571-578 (2008). Web SearchBibTeXDownload
36Top 10 algorithms in data mining. Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus F. M. Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael Steinbach, David J. Hand, Dan Steinberg. Knowl. Inf. Syst. (14): 1-37 (2008). Cited by 78Web SearchBibTeXDownload
2007
35Extension of mixture-of-experts networks for binary classification of hierarchical data. Shu-Kay Ng, Geoffrey J. McLachlan. Artificial Intelligence in Medicine (41): 57-67 (2007). Web SearchBibTeXDownload
34Merging Algorithm to Reduce Dimensionality in Application to Web-Mining. Vladimir Nikulin, Geoffrey J. McLachlan. Australian Conference on Artificial Intelligence 2007, 755-761. Web SearchBibTeXDownload
33Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Jangsun Baek, Young Sook Son, Geoffrey J. McLachlan. Bioinformatics (23): 458-465 (2007). Web SearchBibTeXDownload
32Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution. Geoffrey J. McLachlan, Richard Bean, Liat Ben-Tovim Jones. Computational Statistics & Data Analysis (51): 5327-5338 (2007). Web SearchBibTeXDownload
31Multilevel survival modelling of recurrent urinary tract infections. Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan. Computer Methods and Programs in Biomedicine (87): 225-229 (2007). Web SearchBibTeXDownload
30Two-component Poisson mixture regression modelling of count data with bivariate random effects. Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan. Mathematical and Computer Modelling (46): 1468-1476 (2007). Web SearchBibTeXDownload
2006
29An incremental EM-based learning approach for on-line prediction of hospital resource utilization. Shu-Kay Ng, Geoffrey J. McLachlan, Andy H. Lee. Artificial Intelligence in Medicine (36): 257-267 (2006). Web SearchBibTeXDownload
28A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Geoffrey J. McLachlan, Richard Bean, Liat Ben-Tovim Jones. Bioinformatics (22): 1608-1615 (2006). Web SearchBibTeXDownload
27A Mixture model with random-effects components for clustering correlated gene-expression profiles. Shu-Kay Ng, Geoffrey J. McLachlan, Kui Wang, Liat Ben-Tovim Jones, S.-W. Ng. Bioinformatics (22): 1745-1752 (2006). Web SearchBibTeXDownload
26Mixture Models for Detecting Differentially Expressed Genes in Microarrays. Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu. Int. J. Neural Syst. (16): 353-362 (2006). Web SearchBibTeXDownload
2005
25Normalized Gaussian Networks with Mixed Feature Data. Shu-Kay Ng, Geoffrey J. McLachlan. Australian Conference on Artificial Intelligence 2005, 879-882. Web SearchBibTeXDownload
24Cluster Analysis of High-Dimensional Data: A Case Study. Richard Bean, Geoffrey J. McLachlan. IDEAL 2005, 302-310. Web SearchBibTeXDownload
23Application of Mixture Models to Detect Differentially Expressed Genes. Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu. IDEAL 2005, 422-431. Web SearchBibTeXDownload
2004
22On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples. Geoffrey J. McLachlan, Soong Chang, Jess Mar, Christophe Ambroise, Justin Xi Zhu. APBC 2004, 167-171. Web SearchBibTeXDownload
21Using the EM algorithm to train neural networks: misconceptions and a new algorithm for multiclass classification. Shu-Kay Ng, Geoffrey J. McLachlan. IEEE Transactions on Neural Networks (15): 738-749 (2004). Web SearchBibTeXDownload
20Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Shu-Kay Ng, Geoffrey J. McLachlan. Pattern Recognition (37): 1573-1589 (2004). Web SearchBibTeXDownload
2003
19Model-Based Clustering in Gene Expression Microarrays: An Application to Breast Cancer Data. J. C. Mar, Geoffrey J. McLachlan. APBC 2003, 139-144. Web SearchBibTeXDownload
18Modelling high-dimensional data by mixtures of factor analyzers. Geoffrey J. McLachlan, David Peel, Richard Bean. Computational Statistics & Data Analysis (41): 379-388 (2003). Web SearchBibTeXDownload
17Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees. Shu-Kay Ng, Geoffrey J. McLachlan. DICTA 2003, 145-154. Web SearchBibTeXDownload
16Model-Based Clustering In Gene Expression Microarrays: An Application To Breast Cancer Data. J. C. Mar, Geoffrey J. McLachlan. International Journal of Software Engineering and Knowledge Engineering (13): 579-592 (2003). Web SearchBibTeXDownload
15On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures. Shu-Kay Ng, Geoffrey J. McLachlan. Statistics and Computing (13): 45-55 (2003). Web SearchBibTeXDownload
2002
14A mixture model-based approach to the clustering of microarray expression data. Geoffrey J. McLachlan, Richard Bean, David Peel. Bioinformatics (18): 413-422 (2002). Web SearchBibTeXDownload
13Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachlan, Christine E. McLaren. Machine Learning (47): 7-34 (2002). Web SearchBibTeXDownload
2000
12Mixtures of Factor Analyzers. Geoffrey J. McLachlan, David Peel. ICML 2000, 599-606. Web SearchBibTeX
1999
11Hierarchical Models for Screening of Iron Deficiency Anemia. Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan. ICML 1999, 77-86. Web SearchBibTeX
1998
10Mining in the Presence of Selectivity Bias and its Application to Reject Inference. A. J. Feelders, Soong Chang, Geoffrey J. McLachlan. KDD 1998, 199-203. Web SearchBibTeX
9Robust Cluster Analysis via Mixtures of Multivariate t-Distributions. Geoffrey J. McLachlan, David Peel. SSPR/SPR 1998, 658-666. Web SearchBibTeXDownload
1989
8Bias associated with the discriminant analysis approach to the estimation of mixing proportions. Charles R. O. Lawoko, Geoffrey J. McLachlan. Pattern Recognition (22): 763-766 (1989). Web SearchBibTeXDownload
1988
7Further results on discrimination with autocorrelated observations. Charles R. O. Lawoko, Geoffrey J. McLachlan. Pattern Recognition (21): 69-72 (1988). Web SearchBibTeXDownload
1986
6Asymptotic error rates of the W and Z statistics when the training observations are dependent. Charles R. O. Lawoko, Geoffrey J. McLachlan. Pattern Recognition (19): 467-471 (1986). Web SearchBibTeXDownload
1985
5Discrimination with autocorrelated observations. Charles R. O. Lawoko, Geoffrey J. McLachlan. Pattern Recognition (18): 145-149 (1985). Web SearchBibTeXDownload
1983
4Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function. Charles R. O. Lawoko, Geoffrey J. McLachlan. Pattern Recognition (16): 119-121 (1983). Web SearchBibTeXDownload
1980
3Error rate estimation on the basis of posterior probabilities. S. Ganesalingam, Geoffrey J. McLachlan. Pattern Recognition (12): 405-413 (1980). Web SearchBibTeXDownload
1977
2A note on the choice of a weighting function to give an efficient method for estimating the probability of misclassification. Geoffrey J. McLachlan. Pattern Recognition (9): 147-149 (1977). Web SearchBibTeXDownload
1976
1Further results on the effect of intraclass correlation among training samples in discriminant analysis. Geoffrey J. McLachlan. Pattern Recognition (8): 273-275 (1976). Web SearchBibTeXDownload
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