TY  - GEN
AU  - Maharaj,Elizabeth Ann
AU  - D'Urso,Pierpaolo
AU  - Caiado,Jorge
TI  - Time series clustering and classification
T2  - Computer Science and Data Analysis Series
SN  - 9781498773218
U1  - 000SA.3 23
PY  - 2019///
CY  - Boca Raton
PB  - CRC
KW  - Time Series Analysis
N1  - Includes bibliographical references and index; 1. Introduction -- 2. Time series features and models -- I Unsupervised Approaches: Clustering techniques for Time Series -- 3. Traditional cluster analysis -- 4. Fuzzy clustering -- 5. Observation-based clustering -- 6. Feature-based clustering -- 7. Model-based clustering -- 8. Other time series clustering approaches -- II Supervised Approaches: Classification techniques for Time Series -- 9. feature- based approaches -- 10. Other time series classification approaches -- III Software and Data Sets -- 11. Software and data sets -- Bibliography -- Subject index
N2  - 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.
Features: Provides an overview of the methods and applications of pattern recognition of time series, Covers a wide range of techniques, including unsupervised and supervised approaches, Includes a range of real examples from medicine, finance, environmental science, and more, R and MATLAB code, and relevant data sets are available on a supplementary
ER  -