Howtosignalprocessing
- Which of the application can be used for anomaly detection?
- What are the characteristics of anomaly detection?
- How do I enable anomaly detection?
- What are the data types of anomaly detection?
Which of the application can be used for anomaly detection?
PyOD is an open-source Python library developed specifically for anomaly detection. scikit-learn is an open-source Python library that has built functionality to provide unsupervised anomaly detection.
What are the characteristics of anomaly detection?
Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behavior. These nonconforming patterns are often referred to as anomalies, outliers, discordant observations, exceptions, aberrations, surprises, peculiarities, or contaminants in different application domains [2].
How do I enable anomaly detection?
You can enable Anomaly detection by selecting the chart and adding the “Find Anomalies” option in the analytics pane. For example, let's look at this chart showing Revenue over time. Adding anomaly detection automatically enriches the chart with anomalies and the expected range of values.
What are the data types of anomaly detection?
There are three main classes of anomaly detection techniques: unsupervised, semi-supervised, and supervised. Essentially, the correct anomaly detection method depends on the available labels in the dataset.
