Tom Fawcett
About
Tom Fawcett has authored 25 papers that have received a total of 14.7k indexed citations.
This includes 18 papers in Artificial Intelligence, 9 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. The topics of these papers are Imbalanced Data Classification Techniques (12 papers), Data Mining Algorithms and Applications (8 papers) and Anomaly Detection Techniques and Applications (5 papers). Tom Fawcett is often cited by papers focused on Imbalanced Data Classification Techniques (12 papers), Data Mining Algorithms and Applications (8 papers) and Anomaly Detection Techniques and Applications (5 papers) and collaborates with scholars based in United States, United Kingdom and Japan. Tom Fawcett's co-authors include Foster Provost, Paul Comfort, Ron Kohavi, Salvatore J. Stolfo and Ira J. Haimowitz and has published in prestigious journals such as Machine Learning, The Journal of Strength and Conditioning Research and Pattern Recognition Letters
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