Data Mining When Classes are Imbalanced and Errors Have Costs

PAKDD'2009 Workshop:
Data Mining When Classes are Imbalanced and Errors Have Costs

Monday, April 27, 2009

Bangkok, Thailand


Organizers:

Nitesh Chawla University of Notre Dame (nchawla@cse.nd.edu)
Nathalie Japkowicz University of Ottawa (nat@site.uottawa.ca)
Zhi-Hua Zhou Nanjing University (zhouzh@nju.edu.cn)

Publications and Web Chair:

David Cieslak University of Notre Dame (david.cieslak@gmail.com)



Program Committee:

Gustavo Batista University of Sao Paulo, Brazil
Sanjay Chawla University of Sydney, Australia
David Cieslak University of Notre Dame, USA
Chris Drummond National Research Council, Canada
Seyda Ertekin Penn State University, USA
George Forman HP Labs, USA
Robert Holte University of Alberta, Canada
W. Philip Kegelmeyer Sandia National Labs, USA
Taghi M. Khoshgoftaar Florida Atlantic University, USA
Alek Kolcz Microsoft Research, USA
Miroslav Kubat University of Miami, USA
Charles Ling University of Waterloo, Canada
Xu-Ying Liu Nanjing University, China
Dragos Margineantu Boeing Phantom Works, USA
Stan Matwin University of Ottawa, Canada
Yuchun Tang McAfee, Inc.
Gary Weiss Fordham University, USA