This year's KDD Cup challenge problem is drawn from the domain of medical data mining. The tasks are 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

Download the Gzipped tarball for scoring scripts, test data, raw results, Final PDF rules file, bootstrap vectors, etc.