We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
Rare category analysis is of key importance both in theory and in practice. Previous research work focuses on supervised rare category analysis, such as rare category detection an...
Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene pr...
Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nanshen...
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
A highly skewed microdata contains some sensitive attribute values that occur far more frequently than others. Such data violates the "eligibility condition" assumed by ...
Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Raymond Chi-Win...