Results 91 to 100 of about 20,272,779 (202)

Time Series Classification Based on Fractal Properties

, 2018
The article considers classification task of fractal time series by the meta algorithms based on decision trees. Binomial multiplicative stochastic cascades are used as input time series.
Радівілова, Т. А., Булах, В. А., Кіріченко, Л. О.   +2 more
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Classification of Multifractal Time Series by Decision Tree Methods

, 2018
The article considers classification task of model fractal time series by the methods of machine learning. To classify the series, it is proposed to use the meta algorithms based on decision trees. To modeling the fractal time series, binomial stochastic
Радівілова, Т. А., Булах, В. А., Кіріченко, Л. О.   +2 more
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Time series classification with feature covariance matrices

, 2017
In this work, a novel approach utilizing feature covariance matrices is proposed for time series classification. In order to adapt the feature covariance matrices into time series classification problem, a feature vector is defined for each point in a ...
Ergezer, Hamza, Leblebicioğlu, Mehmet Kemal, Leblebicioglu, Kemal, Hamza Ergezer, Kemal Leblebicioğlu   +4 more
core   +1 more source

SCALE-BOSS-MR: Scalable Time Series Classification Using Multiple Symbolic Representations

Applied Sciences
Time-Series-Classification (TSC) is an important machine learning task for many branches of science. Symbolic representations of time series, especially Symbolic Fourier Approximation (SFA), have been proven very effective for this task, given their ...
Apostolos Glenis, George A. Vouros
doaj   +1 more source

ACTS: An Active Learning Method for Time Series Classification

, 2017
Active learning has been widely used to select the most informative data for labeling in classification tasks, except for time series classification. The main challenge of active learning in time series classification is to evaluate the informativeness ...
Qiong Luo, Peng, Fengchao, Lionel M. Ni, Ni, Lionel M., Fengchao Peng, Luo, Qiong   +5 more
core   +1 more source

Composite Gramian Angular Field for Time-Series Classification

Information
Gramian Angular Field (GAF) encodings transform time series into two-dimensional images suitable for convolutional neural network (CNN) classification. Existing applications typically use either the Gramian Angular Summation Field (GASF) or the Gramian ...
Pero Bogunović, Saša Mladenović, Andrina Granić   +2 more
doaj   +1 more source

Comparative study on time series classification

, 2007
Time series classification or categorization is an important task in time-series analysis. Unlike traditional methods and problem formulations in time-series analysis, time series classification aims to take whole time sequences as input, and produce ...
Pan, Jia Lin, Yang, Yi Ming, Pan, Rong, Yang, Qiang, Li, Lei   +4 more
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Early Classification of Time Series is Meaningful

Many approaches have been proposed for early classification of time series in light of its significance in a wide range of applications including healthcare, transportation and finance.
Achenchabe, Youssef, Cornuéjols, Antoine, Lemaire, Vincent, Bondu, Alexis   +3 more
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Generalized ECG Heartbeat Classification Using Time-Series Transformers

IEEE Access
This research investigates Time-Series Transformer architectures for Electrocardiogram (ECG) heartbeat classification, particularly focusing on their generalization capabilities towards new patients and varying signal sampling rates, a critical challenge
Timo de Waele, Jaron Fontaine, Eli de Poorter, Adnan Shahid   +3 more
doaj   +1 more source

Bag-of-Temporal-SIFT-Words for Time Series Classification

, 2020
. Time series classification is an application of particular interest with the increase of data to monitor. Classical techniques for time series classification rely on point-to-point distances.
Adeline Bailly, Romain Tavenard, Simon Malinowski, Thomas Guyet, Laetitia Chapel   +4 more
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