Results 71 to 80 of about 20,272,779 (202)
On the comparison of time series using subsampling [PDF]
, 2005 In this paper we propose a procedure based on the subsampling techniques for the comparison of stationary time series that are not necessarily independent.
Maharaj, Elizabeth Ann +1 more
core +1 more source
TATS: toolbox for time series data augmentation [PDF]
PeerJ Computer ScienceAugmenting time series data plays a crucial role in enhancing the generalization of classification models, especially in scenarios where labeled datasets are limited.
Dawid Warchoł, Mariusz Oszust
doaj +2 more sources
Classification of non‐stationary time series
Stat, 2014 AbstractIn this paper we consider the problem of classifying non‐stationary time series. The method that we introduce is based on the locally stationary wavelet paradigm and seeks to take account of the fact that there may be within‐class variation in the signals being analysed.
Krzemieniewska, Karolina +2 more
openaire +2 more sources
Patient risk stratification for hospital-associated C. diff as a time-series classification task
, 2019 A patient's risk for adverse events is affected by temporal processes including the nature and timing of diagnostic and therapeutic activities, and the overall evolution of the patient's pathophysiology over time.
Horvitz, Eric +2 more
core
Data Augmentation with Suboptimal Warping for Time-Series Classification
Sensors, 2019 In this paper, a novel data augmentation method for time-series classification is proposed. In the introduced method, a new time-series is obtained in warped space between suboptimally aligned input examples of different lengths.
Krzysztof Kamycki +2 more
doaj +1 more source
Scalable and Explainable Time Series Classification
, 2022 © 2022 Nestor Stiven Cabello WilsonTime series data are ubiquitous, and the explosion of sensor technologies on industry applications has further accelerated their growth.
Cabello Wilson, Nestor Stiven
core +1 more source
Crossfire: cross-domain feature integration for robust time series classification [PDF]
PeerJ Computer ScienceFeature-based time series classification (TSC) methods have traditionally relied on time-domain features, which can limit their effectiveness in capturing the full spectrum of temporal dynamics.
Celal Alagöz
doaj +2 more sources
Time-series clustering via quasi U-statistics
, 2015 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The problem of time-series discrimination and classification is discussed. We propose a novel clustering algorithm based on a
Pinheiro, A, Valk, M
core +1 more source
A Benchmark for Early Time-Series Classification (Extended Abstract)
, 2023 The objective of Early Time-Series Classification (ETSC) is to predict the class of incoming time-series by observing the fewest time-points possible.
Kamberi, Petro-Foti +2 more
core +1 more source
Bayesian time series classification.
, 2016 This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extraction stage and a generative classifier which is built on top of these features. Such two stage approaches are often used in signal and image processing.
Sykacek, P, Roberts, S
openaire +2 more sources