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

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

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 abilities to reduce noise. In this paper, we impro...

Full description

Bibliographic Details
Main Authors: Apostolos Glenis, George A. Vouros
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Applied Sciences
Subjects:
time series
time series classification
symbolic representations
multiple representations
accuracy
execution time
Online Access:https://www.mdpi.com/2076-3417/14/2/689

Internet

https://www.mdpi.com/2076-3417/14/2/689

Similar Items