Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what "suspects" you’re looking for. This O’Reilly report uses practical example to explain how the underlying concepts of anomaly detection work.
Table of contents
- 1. Looking Toward the Future
- 2. The Shape of Anomaly Detection
- 3. Using t-Digest for Threshold Automation
- 4. More Complex, Adaptive Models
- 5. Anomalies in Sporadic Events
- 6. No Phishing Allowed!
- 7. Anomaly Detection for the Future
- A. Additional Resources
- About the Authors
- Title: Practical Machine Learning: A New Look at Anomaly Detection
- Release date: August 2014
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491911600
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