Classifiers and Clustering for Time Series
07 Jan 2024 14:23
Yet Another Inadequate Placeholder
I am especially interested in kernel methods, meaning kernels which define similarity for whole time series trajectories.
See also: Clustering; Time Series
- Recommended (utterly inadequate):
- Eamonn Keogh Jessica Lin, "Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research", Knowledge and Information Systems 8 (2005): 154--177 [PDF preprint via Prof. Keogh]
- Andrew J. Patton, Brian M. Weller, "Testing for Unobserved Heterogeneity via k-means Clustering", arxiv:1907.07582
- To read:
- Marco Cuturi, Arnaud Doucet, "Autoregressive Kernels For Time Series", arxiv:1101.0673 [In which two time series are similar if they are fit by similar autoregressive models]
- Marco Cuturi, Jean-Philippe Vert, Oystein Birkenes, and Tomoko Matsui, "A kernel for time series based on global alignments", cs.CV/0610033
- Madjid Khalilian, Norwati Mustapha, "Data Stream Clustering: Challenges and Issues", arxiv:1006.5261
- Arnost Komárek and Lenka Komárková, "Clustering for multivariate continuous and discrete longitudinal data", Annals of Applied Statistics 7 (2013): 177--200
- Scott Lenser and Manuela Veloso, "Non-Parametric Time Series Classification" [PDF preprint]
- T. Warren Liao, "Clustering of time series data---a survey", Pattern Recognition 38 (2005): 1857--1874
- Zhengdong Lu, Todd K. Leen and Jeffrey Kaye, "Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals", Neural Computation 23 (2011): 2390--2420
- Pierre-Francois Marteau and Sylvie Gibet, "On Recursive Edit Distance Kernels with Application to Time Series Classification", arxiv:1005.5141
- Nishant A. Mehta and Alexander G. Gray, "Generative and Latent Mean Map Kernels", arxiv:1005.0188
- Zoltán Prekopcsák, Daniel Lemire, "Time Series Classification by Class-Based Mahalanobis Distances", arxiv:1010.1526
- Christoph Pamminger and Sylvia Fruühwirth-Schnatter, "Model-based Clustering of Categorical Time Series", Bayesian Analysis 5 (2010): 345--368
- Vitaly Schetinin and Joachim Schult, "Learning Polynomial Networks for Classification of Clinical Electroencephalograms", cs.AI/0504041 [Not a kernel method, at least not to judge by the abstract, but very close to the application domain we have in mind]
- Ansgar Steland, "Optimal sequential kernel detection for dependent processes", Journal of Statistical Planning and Inference 132 (2005): 131--147
- José A. Vilar and Juan M. Vilar, "Time series clustering based on nonparametric multidimensional forecast densities", Electronic Journal of Statistics 7 (2013): 1019--1046
- Bo Zhang, Guangming Pan, Qiwei Yao, Wang Zhou, "Factor Modelling for Clustering High-dimensional Time Series", arxiv:2101.01908