Comparative assessment of automated algorithms for the separation of one-dimensional Gaussian mixtures
Motivation: Gaussian mixture models (GMMs) are probabilistic models commonly used in biomedical research to detect subgroup structures in data sets with one-dimensional information. Reliable model parameterization requires that the number of modes, i.e., states of the generating process, is known. H...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-01-01
|
Series: | Informatics in Medicine Unlocked |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352914822002507 |