Results 31 to 40 of about 576,901 (299)

Deep Multiple Metric Learning for Time Series Classification

IEEE Access, 2021
Effective distance metric plays an important role in time series classification. Metric learning, which aims to learn a data-adaptive distance metric to measure the distance among samples, has achieved promising results on time series classification ...
Zhi Chen, Yongguo Liu, Jiajing Zhu, Yun Zhang, Qiaoqin Li, Rongjiang Jin, Xia He   +6 more
doaj   +1 more source

Time Series Classification Using Images

, 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, Homenda, Wladyslaw, Jastrzebska, Agnieszka   +2 more
core   +1 more source

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, Min Liu, Jiyong Hu, Ping Li, Yali Peng, Yugen Yi   +5 more
doaj   +1 more source

A Metric Learning-Based Univariate Time Series Classification Method

Information, 2020
High-dimensional time series classification is a serious problem. A similarity measure based on distance is one of the methods for time series classification.
Kuiyong Song, Nianbin Wang, Hongbin Wang
doaj   +1 more source

Network Based Sampling for Time Series Classification

, 2021
A time series is an ordered collection of data points collected by observers or sensing devices. Time series classification aims to label time series instances based on previously seen examples.
Samuel T Harford (11713364)
core   +1 more source

Time series classification for varying length series

CoRR, 2019
Research into time series classification has tended to focus on the case of series of uniform length. However, it is common for real-world time series data to have unequal lengths. Differing time series lengths may arise from a number of fundamentally different mechanisms.
Chang Wei Tan, François Petitjean, Eamonn J. Keogh, Geoffrey I. Webb   +3 more
openaire   +2 more sources

Robust explainer recommendation for time series classification. [PDF]

Data Min Knowl Discov
Time series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general sensing.
Nguyen TT, Le Nguyen T, Ifrim G.
europepmc   +2 more sources

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm [PDF]

, 2013
We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data.
Cooke, Emma J., Wild, David L., Robert Darkins, Emma J Cooke, Darkins Robert, Cooke Emma J., Ghahramani Zoubin, Savage, Richard S., Paul D W Kirk, David L Wild, Ghahramani, Zoubin, Kirk Paul D. W., Zoubin Ghahramani, Richard S Savage, Darkins, Robert, Savage Richard S., Kirk, P. (Paul), Wild David L.   +17 more
core   +1 more source

Skewed Time Series Classification Algorithm Based on Persistent Homology [PDF]

Jisuanji gongcheng
To address the limitations of traditional time series classification algorithms to extract high-dimensional topological information and temporal sequence information, this paper proposes a skewed time series classification algorithm based on persistent ...
YAN Yinkai, PENG Ningning, YI Lisha
doaj   +1 more source

Topological Time-series Classification

, 2022
We establish a strong connection between Topological Data Analysis (TDA)and the field of time-series classification. This is accomplished via two novel contri- butions.
Collins, Joseph Robert
core   +1 more source