Geoffrey J. McLachlan

2008
35	EE	Murray A. Jorgensen, Geoffrey J. McLachlan: Wallace's Approach to Unsupervised Learning: The Snob Program. Comput. J. 51(5): 571-578 (2008)
34	EE	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: Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1): 1-37 (2008)
2007
33	EE	Vladimir Nikulin, Geoffrey J. McLachlan: Merging Algorithm to Reduce Dimensionality in Application to Web-Mining. Australian Conference on Artificial Intelligence 2007: 755-761
32	EE	Shu-Kay Ng, Geoffrey J. McLachlan: Extension of mixture-of-experts networks for binary classification of hierarchical data. Artificial Intelligence in Medicine 41(1): 57-67 (2007)
31	EE	Jangsun Baek, Young Sook Son, Geoffrey J. McLachlan: Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Bioinformatics 23(4): 458-465 (2007)
30	EE	Geoffrey J. McLachlan, Richard Bean, Liat Ben-Tovim Jones: Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution. Computational Statistics & Data Analysis 51(11): 5327-5338 (2007)
29	EE	Kui Wang, Kelvin K. W. Yau, Andy H. Lee, Geoffrey J. McLachlan: Multilevel survival modelling of recurrent urinary tract infections. Computer Methods and Programs in Biomedicine 87(3): 225-229 (2007)
2006
28	EE	Shu-Kay Ng, Geoffrey J. McLachlan, Andy H. Lee: An incremental EM-based learning approach for on-line prediction of hospital resource utilization. Artificial Intelligence in Medicine 36(3): 257-267 (2006)
27	EE	Geoffrey J. McLachlan, Richard Bean, Liat Ben-Tovim Jones: A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics 22(13): 1608-1615 (2006)
26	EE	Shu-Kay Ng, Geoffrey J. McLachlan, Kui Wang, Liat Ben-Tovim Jones, S.-W. Ng: A Mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinformatics 22(14): 1745-1752 (2006)
25	EE	Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu: Mixture Models for Detecting Differentially Expressed Genes in Microarrays. Int. J. Neural Syst. 16(5): 353-362 (2006)
2005
24	EE	Shu-Kay Ng, Geoffrey J. McLachlan: Normalized Gaussian Networks with Mixed Feature Data. Australian Conference on Artificial Intelligence 2005: 879-882
23	EE	Richard Bean, Geoffrey J. McLachlan: Cluster Analysis of High-Dimensional Data: A Case Study. IDEAL 2005: 302-310
22	EE	Liat Ben-Tovim Jones, Richard Bean, Geoffrey J. McLachlan, Justin Xi Zhu: Application of Mixture Models to Detect Differentially Expressed Genes. IDEAL 2005: 422-431
2004
21	EE	Geoffrey J. McLachlan, Soong Chang, Jess Mar, Christophe Ambroise, Justin Xi Zhu: On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples. APBC 2004: 167-171
20	EE	Shu-Kay Ng, Geoffrey J. McLachlan: Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Pattern Recognition 37(8): 1573-1589 (2004)
2003
19	EE	J. C. Mar, Geoffrey J. McLachlan: Model-Based Clustering in Gene Expression Microarrays: An Application to Breast Cancer Data. APBC 2003: 139-144
18	EE	Shu-Kay Ng, Geoffrey J. McLachlan: Robust Estimation in Gaussian Mixtures Using Multiresolution Kd-trees. DICTA 2003: 145-154
17	EE	Geoffrey J. McLachlan, David Peel, Richard Bean: Modelling high-dimensional data by mixtures of factor analyzers. Computational Statistics & Data Analysis 41(3-4): 379-388 (2003)
16	EE	J. C. Mar, Geoffrey J. McLachlan: Model-Based Clustering In Gene Expression Microarrays: An Application To Breast Cancer Data. International Journal of Software Engineering and Knowledge Engineering 13(6): 579-592 (2003)
15	EE	Shu-Kay Ng, Geoffrey J. McLachlan: On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures. Statistics and Computing 13(1): 45-55 (2003)
2002
14		Geoffrey J. McLachlan, Richard Bean, David Peel: A mixture model-based approach to the clustering of microarray expression data. Bioinformatics 18(3): 413-422 (2002)
13		Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachlan, Christine E. McLaren: Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Machine Learning 47(1): 7-34 (2002)
2000
12		Geoffrey J. McLachlan, David Peel: Mixtures of Factor Analyzers. ICML 2000: 599-606
1999
11		Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan: Hierarchical Models for Screening of Iron Deficiency Anemia. ICML 1999: 77-86
1998
10		A. J. Feelders, Soong Chang, Geoffrey J. McLachlan: Mining in the Presence of Selectivity Bias and its Application to Reject Inference. KDD 1998: 199-203
9		Geoffrey J. McLachlan, David Peel: Robust Cluster Analysis via Mixtures of Multivariate t-Distributions. SSPR/SPR 1998: 658-666
1989
8	EE	Charles R. O. Lawoko, Geoffrey J. McLachlan: Bias associated with the discriminant analysis approach to the estimation of mixing proportions. Pattern Recognition 22(6): 763-766 (1989)
1988
7	EE	Charles R. O. Lawoko, Geoffrey J. McLachlan: Further results on discrimination with autocorrelated observations. Pattern Recognition 21(1): 69-72 (1988)
1986
6	EE	Charles R. O. Lawoko, Geoffrey J. McLachlan: Asymptotic error rates of the W and Z statistics when the training observations are dependent. Pattern Recognition 19(6): 467-471 (1986)
1985
5	EE	Charles R. O. Lawoko, Geoffrey J. McLachlan: Discrimination with autocorrelated observations. Pattern Recognition 18(2): 145-149 (1985)
1983
4	EE	Charles R. O. Lawoko, Geoffrey J. McLachlan: Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function. Pattern Recognition 16(1): 119-121 (1983)
1980
3	EE	S. Ganesalingam, Geoffrey J. McLachlan: Error rate estimation on the basis of posterior probabilities. Pattern Recognition 12(6): 405-413 (1980)
1977
2	EE	Geoffrey J. McLachlan: A note on the choice of a weighting function to give an efficient method for estimating the probability of misclassification. Pattern Recognition 9(3): 147-149 (1977)
1976
1	EE	Geoffrey J. McLachlan: Further results on the effect of intraclass correlation among training samples in discriminant analysis. Pattern Recognition 8(4): 273-275 (1976)

Coauthor Index

1	Christophe Ambroise	[21]
2	Jangsun Baek	[31]
3	Richard Bean	[14] [17] [22] [23] [25] [27] [30]
4	Igor V. Cadez	[11] [13]
5	Soong Chang	[10] [21]
6	A. J. Feelders	[10]
7	S. Ganesalingam	[3]
8	Joydeep Ghosh	[34]
9	David J. Hand	[34]
10	Liat Ben-Tovim Jones	[22] [25] [26] [27] [30]
11	Murray A. Jorgensen	[35]
12	Vipin Kumar	[34]
13	Charles R. O. Lawoko	[4] [5] [6] [7] [8]
14	Andy H. Lee	[28] [29]
15	Bing Liu	[34]
16	J. C. Mar	[16] [19]
17	Jess Mar	[21]
18	Christine E. McLaren	[11] [13]
19	Hiroshi Motoda	[34]
20	Angus F. M. Ng	[34]
21	S.-W. Ng	[26]
22	Shu-Kay Ng	[15] [18] [20] [24] [26] [28] [32]
23	Vladimir Nikulin	[33]
24	David Peel	[9] [12] [14] [17]
25	J. Ross Quinlan	[34]
26	Padhraic Smyth	[11] [13]
27	Young Sook Son	[31]
28	Michael Steinbach	[34]
29	Dan Steinberg	[34]
30	Kui Wang	[26] [29]
31	Xindong Wu	[34]
32	Qiang Yang	[34]
33	Kelvin K. W. Yau	[29]
34	Philip S. Yu	[34]
35	Zhi-Hua Zhou	[34]
36	Justin Xi Zhu	[21] [22] [25]

Colors in the list of coauthors