April 2014
Intermediate to advanced
334 pages
10h 40m
English
book
Conformal Prediction for Reliable Machine Learning
by Vineeth Balasubramanian, Shen-Shyang Ho, Vladimir Vovk
Content preview from Conformal Prediction for Reliable Machine Learning
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Chapter 4
Anomaly Detection
Rikard Laxhammar, Saab AB, Järfälla, Sweden
Abstract
This chapter presents an extension of conformal prediction for anomaly detection applications. It includes the presentation and discussion of the Conformal Anomaly Detector (CAD) and the computationally more efficient Inductive Conformal Anomaly Detector (ICAD), which are general algorithms for unsupervised or semi-supervised and offline or online anomaly detection. One of the key properties of CAD and ICAD is that the rate of detected anomalies is well calibrated in the online setting under the randomness assumption. Similar to conformal prediction, the choice of Nonconformity Measure (NCM) is of central importance for the classification performance of CAD and ...
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