Results 11 to 20 of about 20,272,779 (202)
Pattern Extraction for Time Series Classification [PDF]
, 2001 In this paper, we propose some new tools to allow machine learning classifiers to cope with time series data. We first argue that many time-series classification problems can be solved by detecting and combining local properties or patterns in time series. Then, a technique is proposed to find patterns which are useful for classification.
Geurts, Pierre, Pierre Geurts
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Technology investigation on time series classification and prediction [PDF]
PeerJ Computer Science, 2022 Time series appear in many scientific fields and are an important type of data. The use of time series analysis techniques is an essential means of discovering the knowledge hidden in this type of data.
Yuerong Tong +9 more
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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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Simulation Study on How Input Data Affects Time-Series Classification Model Results [PDF]
EntropyThis paper discusses the results of a study investigating how input data characteristics affect the performance of time-series classification models. In this experiment, we used 82 synthetically generated time-series datasets, created based on predefined
Maria Sadowska, Krzysztof Gajowniczek
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Eigen-entropy based time series signatures to support multivariate time series classification [PDF]
Scientific ReportsMost current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window ...
Abhidnya Patharkar +6 more
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Adaptive law-based feature representation for time series classification [PDF]
Scientific ReportsTime series classification (TSC) underpins applications across finance, healthcare, and environmental monitoring, yet real-world series often contain noise, local misalignment, and multiscale patterns. We introduce adaptive law-based transformation (ALT),
Marcell T. Kurbucz +4 more
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Time Series Classification Using Images [PDF]
, 2022 This work is a contribution to the field of time series classification. We propose a novel method that transforms time series into multi-channel images, which are then classified using Convolutional Neural Networks as an at-hand classifier.
Wrzesien, Mariusz +2 more
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Classification of Stabilometric Time-Series Using an Adaptive Fuzzy Inference Neural Network System [PDF]
, 2010 Stabilometry is a branch of medicine that studies balance-related human functions. The analysis of stabilometric-generated time series can be very useful to the diagnosis and treatment balance-related dysfunctions such as dizziness.
Caraça-Valente Hernández, Juan Pedro +9 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 ...
Josif Grabocka +2 more
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Time series classification based on statistical features
EURASIP Journal on Wireless Communications and Networking, 2020 This paper presents a statistical feature approach in fully convolutional time series classification (TSC), which is aimed at improving the accuracy and efficiency of TSC.
Yuxia Lei, Zhongqiang Wu
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