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P. Turney. Context-sensitive learning bibliography. Online bibliography, Institute for Information Technology of the National Research Council of Canada, Ottawa, Canada, 1998. http://ai.iit.nrc.ca/- bibliographies/context-sensitive.html.

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Mining Time-Changing Data Streams - Hulten, Spencer, Domingos (2001)   (48 citations)  (Correct)

.... of the journal Machine Learning [28] Other relevant research appeared in the ICML 96 Workshop on Learning in ContextSensitive Domains [15] the AAAI 98 Workshop on AI Approaches to Time Series Problems [8] and the NIPS 2000 Workshop on Real Time Modeling for Complex Learning Tasks [26] Turney [25] maintains an online bibliography on context sensitive learning. 6. FUTURE WORK We plan to apply CVFDT to more real world problems; its ability to adjust to concept changes should allow it to perform very well on a broad range of tasks. CVFDT may be a useful tool for identifying anomalous ....

P. Turney. Context-sensitive learning bibliography. Online bibliography, Institute for Information Technology of the National Research Council of Canada, Ottawa, Canada, 1998. http://ai.iit.nrc.ca/- bibliographies/context-sensitive.html.


MetaCost: A General Method for Making Classifiers Cost-Sensitive - Domingos (1999)   (44 citations)  (Correct)

....it belongs to class j. The realization that in real world applications non uniform costs are the rule rather than the exception has led in recent years to an increased interest in algorithms for cost sensitive classification. Some of these will be discussed in the section on related work; Turney [25] provides an online bibliography on the topic. Substantial work has gone into making individual algorithms cost sensitive. Doing this for all algorithms available in the literature would be a very time consuming enterprise, and often it is far from obvious how best to perform the conversion. A ....

....also suggest that in noisy databases MetaCost may additionally be useful as a method for speeding up learning. 4 Related Work Cost sensitive learning is the subject of a burgeoning literature, which space does not allow us to review here. We point the reader to [15] for a brief review, and to [25] for an online bibliography. This section discusses those elements of previous research that are most closely related to MetaCost. Chan and Stolfo [9] have proposed a variation of stratification that involves learning multiple classifiers on stratified subsamples of the database, which are then ....

P. Turney. Cost-sensitive learning bibliography. Online bibliography, Institute for Information Technology of the National Research Council of Canada, Ottawa, Canada, 1997. http://- ai.iit.nrc.ca/bibliographies/cost-sensitive.html.

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