Anomaly Detection Using Support Vector Machines for Time Series Data
Analysis of large data sets is increasingly important in business and scientific research. One of the challenges in such analysis stems from uncertainty in data, which can produce anomalous results. This paper proposes a method for detecting an anomaly in time series data using a Support Vector Mach...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2021-05-01
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| Series: | Journal of Robotics, Networking and Artificial Life (JRNAL) |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125957120/view |