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KAIS
2010
144views more  KAIS 2010»
14 years 10 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 8 days ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
ICDE
2002
IEEE
204views Database» more  ICDE 2002»
16 years 1 months ago
Approximating a Data Stream for Querying and Estimation: Algorithms and Performance Evaluation
Obtaining fast and good quality approximations to data distributions is a problem of central interest to database management. A variety of popular database applications including,...
Sudipto Guha, Nick Koudas
SDM
2007
SIAM
131views Data Mining» more  SDM 2007»
15 years 1 months ago
Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
Yijian Bai, Haixun Wang, Carlo Zaniolo
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 1 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...