| KDD Cup |
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Task Overview
The KDDCup-2006 challenge problem was drawn from the domain of medical data mining. The tasks involve a series of Computer-Aided Detection problems revolving around the clinical problem of identifying pulmonary embolisms from three-dimensional computed tomography data. This challenging domain is characterized by:
- Multiple instance learning
- Non-IID examples
- Nonlinear cost functions
- Skewed class distributions
- Noisy class labels
- Sparse data
Task Rules, FAQs, etc
- KDD Cup 2006 Rules
- KDD Cup 2006 Submission Rules
- KDD Cup 2006 FAQ
- Final version of data description, task specification, and rules (v. 1.1) (PDF format, 303 KB)
- Initial data description, task specification, and rules (v. 1.0)(PDF format, 211 KB)
- Gzipped tarball including scoring scripts, test data, raw results, Final PDF rules file, bootstrap vectors,etc. (3.37 Meg)
Task Results
Acknowledgements
Many thanks to Siemens Medical Solutions for providing the CAD data sets, task specifications, and data expertise.
Original Site
