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ICDM
2006
IEEE
84views Data Mining» more  ICDM 2006»
14 years 1 months ago
Exploratory Under-Sampling for Class-Imbalance Learning
Under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. The main deficiency is that many major class exa...
Xu-Ying Liu, Jianxin Wu, Zhi-Hua Zhou
PAMI
2008
302views more  PAMI 2008»
13 years 7 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos
ICDM
2010
IEEE
154views Data Mining» more  ICDM 2010»
13 years 5 months ago
Discrimination Aware Decision Tree Learning
Abstract--Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute , find a classifier with high predictive accu...
Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
ECAI
1998
Springer
13 years 12 months ago
Integrating Abduction and Induction
In this paper we describe an approach for integrating abduction and induction in the ILP setting of learning from interpretations with the aim of solving the problem of incomplete...
Fabrizio Riguzzi
ICSE
1995
IEEE-ACM
13 years 11 months ago
Reverse Engineering of Legacy Code Exposed
— Reverse engineering of large legacy software systems generally cannot meet its objectives because it cannot be cost-effective. There are two main reasons for this. First, it is...
Bruce W. Weide, Wayne D. Heym, Joseph E. Hollingsw...