Date of Completion

12-2-2019

Embargo Period

12-2-2019

Keywords

Topological data analysis, time series, clustering, classification

Major Advisor

Nalini Ravishanker

Associate Advisor

Zhiyi Chi

Associate Advisor

Haim Bar

Field of Study

Statistics

Degree

Doctor of Philosophy

Open Access

Open Access

Abstract

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.

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