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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 7 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
SADM
2010
141views more  SADM 2010»
13 years 1 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
CSDA
2007
137views more  CSDA 2007»
13 years 7 months ago
Fitting finite mixtures of generalized linear regressions in R
R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested var...
Bettina Grün, Friedrich Leisch
ESANN
2004
13 years 8 months ago
Flexible and Robust Bayesian Classification by Finite Mixture Models
Abstract. The regularized Mahalanobis distance is proposed in the framework of finite mixture models to avoid commonly faced numerical difficulties encountered with EM. Its princip...
Cédric Archambeau, Frédéric V...
TIP
2002
179views more  TIP 2002»
13 years 6 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki