What is an anomaly?
- An anomaly is something that differs from what is typical, normal, or expected. It can be an irregularity or an outlier that stands out from the usual pattern. Anomalies are important because they often signal unusual or unexpected events, such as errors, fraud, or rare incidents.
- Anomaly detection involves identifying these uncommon patterns or outliers within a dataset. This process finds applications in various fields, including fraud detection, network security, healthcare, manufacturing, and more.
Support Vector Machine (SVM) for Anomaly Detection
Support Vector Machines (SVMs) are powerful supervised learning models that can also be used for anomaly detection. They can be effective for anomaly detection because they find the hyperplane that best separates the normal data points from the anomalies.
Mainly, the one-class support vector machine is an unsupervised model for anomaly or outlier detection. In this article, we will discuss how we can use support vector machines for anomaly detection.