Exploring interval implicitization in real-valued time series classification and its applications

Due to the fact of uncertainty contained in observed real-valued time series, the aim of this paper is to explore interval implicitization in real-valued time series classification problems. A novel real-valued time series classification method under the transformed implicit interval-valued data env...

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Bibliographic Details
Published in:The Journal of supercomputing Vol. 79; no. 3; pp. 3373 - 3391
Main Authors: Tao, Zhifu, Yao, Bingxin, Zhu, Jiaming
Format: Journal Article
Language:English
Published: New York Springer US 01.02.2023
Springer Nature B.V
Subjects:
Algorithms
Classification
Compilers
Computer Science
Datasets
Decomposition
Interpreters
Methods
Neural networks
Processor Architectures
Programming Languages
Time series
Interval-valued time series
ARIMA
Dynamic time warping
Time series
Classification
ISSN:0920-8542, 1573-0484
Online Access:Get full text
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