Results 161 to 170 of about 303,598 (207)

Time-series clustering for home dwell time during COVID-19: what can we learn from it?

, 2020
Huang X, Li Z, Lu J, Wang S, Wei H, Chen B.   +5 more
europepmc   +1 more source

Clustering methods for categorical time series and sequences : a scoping review. [PDF]

BMC Med Res Methodol
Khalifa O, Balendran A, Tran VT, Petit F.   +3 more
europepmc   +1 more source

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Clustering of time series data—a survey

Pattern Recognition, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
T Warren Liao
exaly   +3 more sources

Deep Time-Series Clustering: A Review [PDF]

Electronics (Switzerland), 2021
We present a comprehensive, detailed review of time-series data analysis, with emphasis on deep time-series clustering (DTSC), and a case study in the context of movement behavior clustering utilizing the deep clustering method. Specifically, we modified
Ali Alqahtani, Mohammed Ali, Xianghua Xie   +2 more
exaly   +2 more sources

Clustering of interval time series

Statistics and Computing, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elizabeth Ann Maharaj, Paulo Teles 0001, Paula Brito   +2 more
openaire   +2 more sources

The time series cluster kernel

2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP), 2017
This paper presents the time series cluster kernel (TCK) for multivariate time series with missing data. Our approach leverages the missing data handling properties of Gaussian mixture models (GMM) augmented with empirical prior distributions. Further, we exploit an ensemble learning approach to ensure robustness to parameters by combining the ...
Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz, Robert Jenssen   +3 more
openaire   +1 more source

Cluster of Time Series

Journal of Classification, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Spectral Clustering for Time Series

2005
This paper presents a general framework for time series clustering based on spectral decomposition of the affinity matrix. We use the Gaussian function to construct the affinity matrix and develop a gradient based method for self-tuning the variance of the Gaussian function.
Fei Wang 0001, Changshui Zhang
openaire   +1 more source