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Time Series Clustering and Classification. 時系列クラスタリングと分類
・ISBN 978-1-4987-7321-8 2019 hard GB£ 187.99
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・ISBN 978-1-032-09349-9 2021 paper GB£ 53.99
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-0-429-05826-4
| 著者・編者 | Maharaj, Elizabeth Ann / D'Urso, P. / Caiado, J., |
|---|---|
| シリーズ | Chapman & Hall/CRC Computer Science and Data Analysis |
| 出版社 | (Chapman & Hall / CRC, US) |
| ページ数 | 228 pp. |
| 言語 | ENG |
| ニュース番号 | ＜649-426 649-P959＞ |
解説
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.
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 website