Definition
Novelty detection is a machine learning task focused on identifying data points that do not conform to expected behavior or known classes. It typically operates in an unsupervised manner, learning the distribution of normal data during training. When new data arrives, the model flags instances that deviate substantially from this learned norm. This is crucial for anomaly detection in security, fraud prevention, and quality control where rare events must be caught without prior labeled examples.
Summary
An unsupervised learning technique used to identify new or unknown patterns that differ significantly from established training data.
Key Concepts
- Unsupervised Learning
- Anomaly Detection
- Outlier Detection
- Distribution Modeling
Use Cases
- Cybersecurity intrusion detection
- Manufacturing defect identification
- Financial fraud monitoring