Hunt, L., and Jorgensen, J. (1997). Mixture model clustering: a brief introduction to the MULTIMIX program. Unpublished manuscript. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
The Emmix Software For The Fitting Of Mixtures Of.. - McLachlan, Peel.. (Correct)
....mixtures have been reviewed recently by Haughton (1997) Also, Wallace and Dowe (1994) have considered the application of their SNOB (http: www.cs. monash.edu.au dld Snob.html) program to mixture modelling using the minimum message length principle of Wallace and Boulton (1968) More recently, Hunt and Jorgensen (1997) have developed the MULTIMIX program for the fitting of mixture models to data sets that contain categorical and continuous variables and that may have missing values. Under the assumption that y 1 ; y n are independent realizations of the feature vector Y , the log likelihood function ....
Hunt, L., and Jorgensen, J. (1997). Mixture model clustering: a brief introduction to the MULTIMIX program. Unpublished manuscript.
Bayesian Latent Semantic Analysis - de Freitas, Barnard (2000) (Correct)
.... either eigen vector analysis, K means or agglomerative hierarchical methods, have proved to be very popular in elds such as information retrieval, data mining, biology, image segmentation and epidemiology (Baeza Yates and Ribeiro Neto 1999, Cadez, Ga ney and Smyth 2000, Hofmann and Puzicha 1998, Hunt and Jorgensen 1999, Shi and Malik 1997) There are a few reasons for this popularity. Firstly, by grouping similar items together, one is intrinsically performing data compression. This task is of paramount importance when managing massive databases. For instance, to process a query eciently, it is easier to search ....
....on images, ltering objectionable images, copy detection for intellectual property protection, fashion catalogues, artist s databases, etc. Several authors have, however, stated that traditional clustering techniques can be very sensitive to variations in the data (Andr es Christen et al. 2000, Hunt and Jorgensen 1999). In addition, it is not straightforward to design distance measures or to choose similarity levels in hierarchical schemes. Despite these shortcomings, traditional clustering methods have enjoyed some reasonable success. Mixture models, which are rooted on a more satisfactory theoretical ....
[Article contains additional citation context not shown here]
Hunt, L. A. and Jorgensen, M. A. (1999). Mixture model clustering: A brief introduction to the MULTIMIX program, Australian and New Zealand Journal of Statistics 40: 153{ 171.
The Emmix Software For The Fitting Of Mixtures Of.. - Mclachlan, Peel.. (1999) (Correct)
....been reviewed recently by Haughton (1997) Also, Wallace and Dowe (1994) have considered the application of their SNOB (http: www.cs. monash.edu.au lloyd tildeMML Notes SNOB.html) program to mixture modelling using the minimum message length principle of Wallace and Boulton (1968) More recently, Hunt and Jorgensen (1997) have developed the MULTIMIX program for the fitting of mixture models to data sets that contain categorical and continuous variables and that may have missing values. Under the assumption that y 1 ; y n are independent realizations of the feature vector Y , the log likelihood function ....
Hunt, L., and Jorgensen, J. (1997). Mixture model clustering: a brief introduction to the MULTIMIX program. Unpublished manuscript.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC