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Time Series Clustering and Classification [PDF]
, 2019 Questo libro contiene informazioni ottenute da fonti autentiche e apprezzate. Sono stati compiuti sforzi ragionevoli per pubblicare dati e informazioni affidabili, ma l'autore e l'editore non possono assumersi la responsabilità€ della validità€ di tutti i materiali o delle conseguenze del loro utilizzo.
E. A. Maharaj +2 more
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Discriminative Dictionary Learning for Time Series Classification
IEEE Access, 2020 Time series symbolization based on the Symbolic Fourier Approximation (SFA) and a sliding window mechanism can effectively improve classification performance. Hence, it has become a research hotspot of time series representation learning.
Wei Zhang +3 more
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Invariant Time-Series Classification [PDF]
, 2012 Time-series classification is a field of machine learning that has attracted considerable focus during the recent decades. The large number of time-series application areas ranges from medical diagnosis up to financial econometrics. Support Vector Machines (SVMs) are reported to perform non-optimally in the domain of time series, because they suffer ...
Grabocka, Josif +2 more
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Time series classification based on triadic time series motifs [PDF]
International Journal of Modern Physics B, 2019 It is of great significance to identify the characteristics of time series to quantify their similarity and classify different classes of time series. We define six types of triadic time-series motifs and investigate the motif occurrence profiles extracted from the time series.
Wen-Jie Xie, Rui-Qi Han, Wei-Xing Zhou
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Emotional Expression Classification Using Time-Series Kernels [PDF]
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2013 Estimation of facial expressions, as spatio-temporal processes, can take advantage of kernel methods if one considers facial landmark positions and their motion in 3D space. We applied support vector classification with kernels derived from dynamic time-warping similarity measures.
Lorincz, A +4 more
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Hierarchical Factor Classification of Dendrochronological Time-Series
Annals of Silvicultural Research, 2020 In this paper, Hierarchical Factor Classification (HFC), an exploratory method of classification of characters is introduced, in comparison with Principal Component Analysis (PCA) in order to show its advantages, in particular when dealing with time ...
Sergio Camiz +3 more
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Time Series Classification Based on Multi-Dimensional Feature Fusion
IEEE Access, 2023 Time series classification is a key problem in data mining, most of existing classification methods directly extract one-dimensional data from one-dimensional features, which cannot effectively express the inter-relation between different time points ...
Shuo Quan +4 more
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Multivariate LSTM-FCNs for time series classification [PDF]
Neural Networks, 2019 Over the past decade, multivariate time series classification has received great attention. We propose transforming the existing univariate time series classification models, the Long Short Term Memory Fully Convolutional Network (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN), into a multivariate time series classification model by augmenting the fully ...
Karim, Fazle +3 more
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Time series classification with Echo Memory Networks [PDF]
Neural Networks, 2019 Echo state networks (ESNs) are randomly connected recurrent neural networks (RNNs) that can be used as a temporal kernel for modeling time series data, and have been successfully applied on time series prediction tasks. Recently, ESNs have been applied to time series classification (TSC) tasks.
Qianli Ma +3 more
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LA-ESN: A Novel Method for Time Series Classification
Information, 2023 Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ...
Hui Sheng +5 more
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