Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning of the relevant patterns This dissertation proposes TS representations and methods for supervised TS analysis.
Download count: 0
- Partial requirement for: Ph.D., Arizona State University, 2012Note typethesis
- Includes bibliographical references (p. 164-175)Note typebibliography
- Field of study: Industrial engineering