What is an anomaly?

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....

Why do we use Support Vector Machines for Anomaly Detection?

We use Support Vector Machine for anomaly detection because of the following reasons:...

Implementation of using Support Vector Machines for anomaly detection

To demonstrate how to use Support Vector Machines for anomaly detection we will use a sample dataset....

Conclusion

In conclusion, One-Class SVMs are highly effective for anomaly detection due to their ability to handle high-dimensional and imbalanced data while providing robust decision boundaries. By tuning hyperparameters and decision thresholds, these models can accurately identify and separate anomalies from normal data points, making them invaluable in fields such as fraud detection, network security, and healthcare. This approach demonstrates how SVMs can be leveraged to detect rare and unusual events within a dataset....