# What Is anomaly detection? An anomaly is something that deviates from expectations. If you had a collection of Granny Smith green apples and there was one blue apple in there, the blue apple is an anomaly. Is it something to be concerned about? Blue apples are highly unusual, in fact,...
Defining “anomaly” is not easy.That’s because the answers often are not black/white issues: instead, there’s many shades of grey. First, the notion of “anomaly” deviates highly between the application of and the sensitivity of the situation. An example: An unauthorized login attempt by...
Unsupervised methods of anomaly detection detect anomalies in an unlabeled test set of data based solely on the intrinsic properties of that data. The working assumption is that, as in most cases, the large majority of the instances in the data set will be normal. The anomaly detection algorith...
Understanding the types of outliers that an anomaly detection system can identify is essential to getting the most value from generated insights. Without knowing what you’re up against, you risk making the wrong decisions once your anomaly detection system alerts you to an issue or opportunity....
However, anomaly detection has its unique challenges in healthcare. One issue is that it can be difficult to establish the baseline (i.e., the normal behavior) when it comes to different medical diagrams. For instance, an electroencephalogram of a healthy person varies based on individual charac...
Using an anomaly detection system to detect data anomalies is a critical aspect of data analysis, ensuring that the findings are accurate and reliable. Various anomaly detection methods can be used in building an anomaly detection system.
Explainability.Is it enough to determine if an anomalous event has occurred, or should priority be given to algorithms that can explain contributing factors, even if they are not as accurate? Anomaly detection tools and software Anomaly detection is generally baked into most modern security, IT man...
Application performance anomaly detection aims to reduce three key incident metrics; The mean time to detect (MTTD) is when an anomaly occurs. The mean time to investigate (MTTI) is the cause of the issue. And themean time to resolution (MTTR)is about how long it takes to resolve the iss...
What Is Anomaly Detection?In this chapter, you will learn about anomalies in general, the categories of anomalies, and anomaly detection. You will also learn why anomaly detection is important and how anomalies can be detected and the use case for such a mechanism....
Anomaly detection is mainly a data-mining process and is used to determine the types of anomalies occurring in a given data set and to determine details about their occurrences. It is applicable in domains such as fraud detection, intrusion detection, fault detection, system health monitoring and...