Time Series Clustering with an EM algorithm for Mixtures of Linear Gaussian State Space Models
基于线性高斯状态空间混合模型与 EM 算法的时间序列聚类
In this paper, we consider the task of clustering a set of individual time series while modeling each cluster, that is, model-based time series clustering. The task requires a parametric model with sufficient flexibility to describe the dynamics in various time series. To address this problem, we propose a novel model-based time series clustering method with mixtures of linear Gaussian state space models, which have high flexibility. The proposed method uses a new…