Lung Cancer Data Set

Below are papers that cite this data set, with context shown. Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info.

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Jinyan Li and Limsoon Wong. Using Rules to Analyse Bio-medical Data: A Comparison between C4.5 and PCL. WAIM. 2003.

[15], it is aimed to classify tumor and normal cells for diagnostic purpose; while in the lung cancer data set [9], it is aimed to differentiate two types of disease. We use Table 4 to summarize the background information of 6 data sets for the subtype classification of the childhood leukemia disease. All

Manoranjan Dash and Huan Liu. Hybrid Search of Feature Subsets. PRICAI. 1998.

having a large N and a small M values such as Lung Cancer Promoters, Soybean, Splice datasets ABB takes very long time (a number of hours) to terminate. For datasets having large N value and substantially big M value such as Splice dataset FocusM takes many hours to terminate. The

Glenn Fung and Sathyakama Sandilya and R. Bharat Rao. Rule extraction from Linear Support Vector Machines. Computer-Aided Diagnosis & Therapy, Siemens Medical Solutions, Inc.

including a medical dataset on detection of lung cancer from medical images. The ability to convert SVM's and other "black-box" classifiers into a set of human-understandable rules, is critical not only for physician