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Abstract: During a project examining the use of machine learning techniques for oil spill detection, we encountered several essential questions that we believe deserve the attention of the research community. We use our particular case study to illustrate such issues as problem formulation, selection of evaluation measures, and data preparation. We relate these issues to properties of the oil spill application, such as its imbalanced class distribution, that are shown to be common to many applications.... (Update)
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...validation process is repeated 10 times for each dataset and classifier. The results of 5This approach has some precedent. Kubat et al. [3] assess likely classifier accuracy by grouping data in known batches then running a type of restricted cross validation, in which a single...
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BibTeX entry: (Update)
Kubat, M., Holte, R. C., & Matwin, S. (1998). Machine learning for the detection of oil spills in satellite radar images. Machine Learning, 30 (2/3). http://citeseer.ist.psu.edu/article/kubat98machine.html More
@article{ kubat98machine,
author = "Miroslav Kubat and Robert C. Holte and Stan Matwin",
title = "Machine Learning for the Detection of Oil Spills in Satellite Radar Images",
journal = "Machine Learning",
volume = "30",
number = "2-3",
pages = "195-215",
year = "1998",
url = "citeseer.ist.psu.edu/article/kubat98machine.html" }
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