Cargando…
A Batch Rival Penalized Expectation-Maximization Algorithm for Gaussian Mixture Clustering with Automatic Model Selection
Within the learning framework of maximum weighted likelihood (MWL) proposed by Cheung, 2004 and 2005, this paper will develop a batch Rival Penalized Expectation-Maximization (RPEM) algorithm for density mixture clustering provided that all observations are available before the learning process. Com...
Autores principales: | Wen, Jiechang, Zhang, Dan, Cheung, Yiu-ming, Liu, Hailin, You, Xinge |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287038/ https://www.ncbi.nlm.nih.gov/pubmed/22400050 http://dx.doi.org/10.1155/2012/425730 |
Ejemplares similares
-
The Discrete Gaussian Expectation Maximization (Gradient) Algorithm for Differential Privacy
por: Wu, Weisan
Publicado: (2021) -
Data on MRI brain lesion segmentation using K-means and Gaussian Mixture Model-Expectation Maximization
por: Qiao, Ju, et al.
Publicado: (2019) -
Expectation-Maximization Algorithm for the Calibration of Complex Simulator Using a Gaussian Process Emulator
por: Seo, Yun Am, et al.
Publicado: (2020) -
Combined Gaussian Mixture Model and Pathfinder Algorithm for Data Clustering
por: Huang, Huajuan, et al.
Publicado: (2023) -
Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields
por: Yousefi, Siamak, et al.
Publicado: (2016)