An adaptive optimization method for estimating the number of components in a Gaussian mixture model

被引：1
|
作者：
Sun, Shuping [1 ]
Tong, Yaonan [1 ]
Zhang, Biqiang [2 ]
Yang, Bowen [3 ]
He, Peiguang [2 ]
Song, Wei [1 ]
Yang, Wenbo [2 ]
Wu, Yilin [4 ]
Liu, Guangyu [2 ]
机构：
[1] Hunan Inst Sci & Technol, Sch Informat Sci & Engn, Yueyang 414006, Peoples R China
[2] Nanyang Inst Technol, Dept Informat Engn, Nanyang 473004, Peoples R China
[3] Univ Chinese Acad Sci UCAS, Sch Integrated Circuits, Beijing 101400, Peoples R China
[4] Nanyang Inst Technol, Dept Intelligent Mfg, Nanyang 473004, Peoples R China
来源：
JOURNAL OF COMPUTATIONAL SCIENCE | 2022年 / 64卷
关键词：
GMM; MIGMM; chi(2) distribution; Mahalanobis distance; Adaptive optimal number; Adaptive interval; IMPROVED EM ALGORITHM; INFORMATION CRITERION; ORDER SELECTION; CREDIT RISK; K-MEANS; IDENTIFICATION; PREDICTION; APPROXIMATION; SYSTEMS;
D O I：
10.1016/j.jocs.2022.101874
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Regarding the determination of the number of components (M) in a Gaussian mixture model (GMM), this study proposes a novel method for adaptively locating an optimal value of M when using a GMM to fit a given dataset; this method avoids underfitting and overfitting due to an unreasonable manually specified interval. The major contributions of this study are highlighted: (1) An adaptive interval for M (denoted as M is an element of [M-Min(Ada), M-Max(Ada)]) based on two procedures of a novel method, the modified incremental Gaussian mixture model (MIGMM), is determined via an adjustable parameter beta. (2) Considering some typical criteria, the optimal number.. within the obtained adaptive interval [M-Min(Ada), M-Max(Ada)], M-Opt(Ada) , is ultimately determined. Regarding the adaptive interval, extensive experiments with typical synthetic datasets show that [M-Min(Ada) M-Max(Ada)], corresponding to the parameter [beta(Min) = 10(-11), beta(Max) = 10(-2)], is determined. The performance of the M-Opt(Ada) determination based on several typical criteria is evaluated on both synthetic and real-world datasets.
引用
收藏
页数：15
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