Fuzzy Jump Models for Soft and Hard Clustering of Multivariate Time Series Data
多变量时间序列软聚类与硬聚类的模糊跳跃模型
Statistical jump models have been recently introduced to detect persistent regimes by clustering temporal features and discouraging frequent regime changes. However, they are limited to hard clustering and thereby do not account for uncertainty in state assignments. This work presents an extension of the statistical jump model that incorporates uncertainty estimation in cluster membership. Leveraging the similarities between statistical jump models and the fuzzy c-means…