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IPM
2008
196views more  IPM 2008»
13 years 7 months ago
Author identification: Using text sampling to handle the class imbalance problem
Authorship analysis of electronic texts assists digital forensics and anti-terror investigation. Author identification can be seen as a single-label multi-class text categorizatio...
Efstathios Stamatatos
ISDA
2010
IEEE
13 years 5 months ago
Comparing SVM ensembles for imbalanced datasets
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal
ICIC
2005
Springer
14 years 1 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao
DATAMINE
2006
117views more  DATAMINE 2006»
13 years 7 months ago
A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs
Effective information systems require the existence of explicit process models. A completely specified process design needs to be developed in order to enact a given business proce...
Laura Maruster, A. J. M. M. Weijters, Wil M. P. va...
DATAMINE
2008
143views more  DATAMINE 2008»
13 years 7 months ago
Automatically countering imbalance and its empirical relationship to cost
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...