Features

Announcing the 2006 KDD Cup data mining challenge

Chair: Terran Lane (University of New Mexico)

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

http://www.cs.unm.edu/kdd_cup_2006

Timeline:
May 15: Release of KDD Cup Specification v. 1.0; availability of preliminary training data.
July 10: Submission mechanism open.
July 17: End of results submission phase.
Aug 1: Results announced.
Aug 23-26: KDD

Many thanks to Siemens Medical Solutions for providing the CAD data sets, task specifications, and data expertise.