Elizabeth Ann Maharaj, Pierpaolo D'Urso, Jorge Caiado
Chapman and Hall/CRC
March 11, 2019 Forthcoming
Reference - 228 Pages - 46 B/W Illustrations
ISBN 9781498773218 - CAT# K29548
Series: Chapman & Hall/CRC Computer Science & Data Analysis
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data.
Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students.
Time Series Features and Models
Traditional cluster analysis
Other time series clustering approaches
Other time series classification approaches
Software and Data Sets