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
Time series clustering and classification
β Scribed by Caiado, Jorge; D'Urso, Pierpaolo; Maharaj, Elizabeth Ann
- Publisher
- CRC Press
- Year
- 2019
- Tongue
- English
- Leaves
- 245
- Series
- Chapman et Hall/CRC computer science and data analysis series
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Dedications......Page 6
Contents......Page 8
Preface......Page 14
Authors......Page 16
1 Introduction......Page 18
2 Time series features and models......Page 26
Part I: Unsupervised Approaches: Clustering Techniques for Time Series......Page 44
3 Traditional cluster analysis......Page 46
4 Fuzzy clustering......Page 54
5 Observation-based clustering......Page 66
6 Feature-based clustering......Page 84
7 Model-based clustering......Page 128
8 Other time series clustering approaches......Page 170
Part II: Supervised Approaches: Classification Techniques for Time Series......Page 180
9 Feature-based approaches......Page 182
10 Other time series classification approaches......Page 208
Part III: Software and Data Sets......Page 214
11 Software and data sets......Page 216
Bibliography......Page 222
Subject index......Page 242
β¦ Subjects
Cluster-Analyse;Cluster analysis;Klassifikation;Maschinelles Lernen;Time-series analysis;Zeitreihe
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