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City Las Vegas / San Francisco / / Company Twentieth Intl / Neural Information Processing Systems / MIT Press / / Continent Asia / / Country Japan / United States / / Currency USD / / / Event Product Recall / Product Issues / / Facility Categorical Datasets Kaustav Das Machine Learning Department Carnegie Mellon University / Public Policy Carnegie Mellon University / Jeff Schneider Machine Learning Department Carnegie Mellon University / / IndustryTerm real-world applications / anomalous pattern detection algorithm / reinsertion algorithm / pattern detection algorithm / anomaly pattern detection algorithm / pattern search / internet-based services / local anomaly detection algorithms / Internet security / maximum product / data mining / detection algorithm / search operator / / Organization Daniel B. Neill Heinz School / National Science Foundation / MIT / Carnegie Mellon University Pittsburgh PA / / Person Daniel B. Neill / Jeff Schneider / Morgan Kaufmann / / / Position Use Fisher / Fisher / Data Mining General / / Product 0.3 0.5 0.4 0.3 0.2 0.1 0.1 0.4 0.6 Detection Rate/ / Detection Rate/ / 0.7 0.6 0.5 0.4 0.3 0.2 0.2 0.4 0.6 Detection Rate/ / 0.2 0.4 0.6 Detection Rate/ / / ProvinceOrState Nevada / Allegheny / California / / PublishedMedium Machine Learning / Journal of Artificial Intelligence Research / / Technology 2.3 Algorithm / local anomaly detection algorithms / WSARE algorithm / pattern detection algorithm / anomaly pattern detection algorithm / artificial intelligence / anomalous pattern detection algorithm / Data Mining / Machine Learning / simulation / AD Tree building algorithm / reinsertion algorithm / detection algorithm / / SocialTag 
Anomaly Pattern Detection in Categorical Datasets Kaustav Das Machine Learning Department Carnegie Mellon University Pittsburgh PA 15203