Name
Title | ||
|---|---|---|
Feature expansion of single dimensional time series data for machine learning classification |
Abstract | ||
|---|---|---|
In this paper, we propose a feature expansion approach for the lowest one-dimension (1-D) time series data classification problems, where the expanded features include temporal, frequency, and statistical characteristics. We show that the proposed feature expansion can improve the classification accuracy compared to conventional machine learning algorithms for data classification. This is because ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICUFN49451.2021.9528690 | 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN) |
Keywords | DocType | ISSN |
Time-frequency analysis,Machine learning algorithms,Statistical analysis,Time series analysis,Transforms,Machine learning,Feature extraction | Conference | 2165-8528 |
ISBN | Citations | PageRank |
978-1-7281-6476-2 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daeun Jung | 1 | 0 | 0.34 |
| jungjin lee | 2 | 30 | 3.05 |
| Hyunggon Park | 3 | 229 | 24.11 |