Topological Data Analysis for Clustering and Classifying Time Series
Renjie Chen · OpenCommons at University of Connecticut (University of Connecticut) · 2019
Topological Data Analysis (TDA), which refers to methods of utilizing topological features in data (such as connected components, tunnels, voids, etc.) has gained considerable momentum. More recently, TDA has been increasingly used for analyzing time series. The recent researches of using TDA in time series are mainly focused on unsupervised and supervised learning. In this thesis, a review of TDA will be provided, following by using TDA in time series for doing unsupervised and supervised learning for different applications.