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» Hybrid Learning Scheme for Data Mining Applications
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KAIS
2010
144views more  KAIS 2010»
13 years 6 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
ICDM
2008
IEEE
164views Data Mining» more  ICDM 2008»
14 years 2 months ago
Classifying High-Dimensional Text and Web Data Using Very Short Patterns
In this paper, we propose the "Democratic Classifier", a simple, democracy-inspired patternbased classification algorithm that uses very short patterns for classificatio...
Hassan H. Malik, John R. Kender
KDD
2009
ACM
211views Data Mining» more  KDD 2009»
14 years 8 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
GECCO
2003
Springer
167views Optimization» more  GECCO 2003»
14 years 1 months ago
Dimensionality Reduction via Genetic Value Clustering
Abstract. Feature extraction based on evolutionary search offers new possibilities for improving classification accuracy and reducing measurement complexity in many data mining and...
Alexander P. Topchy, William F. Punch
CVPR
2011
IEEE
13 years 5 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...