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ICDM
2006
IEEE
129views Data Mining» more  ICDM 2006»
16 years 1 months ago
Getting the Most Out of Ensemble Selection
We investigate four previously unexplored aspects of ensemble selection, a procedure for building ensembles of classifiers. First we test whether adjusting model predictions to p...
Rich Caruana, Art Munson, Alexandru Niculescu-Mizi...
ICDM
2006
IEEE
146views Data Mining» more  ICDM 2006»
16 years 1 months ago
Boosting Kernel Models for Regression
This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Ping Sun, Xin Yao
ICDM
2006
IEEE
127views Data Mining» more  ICDM 2006»
16 years 1 months ago
Optimal k-Anonymity with Flexible Generalization Schemes through Bottom-up Searching
In recent years, a major thread of research on kanonymity has focused on developing more flexible generalization schemes that produce higher-quality datasets. In this paper we in...
Tiancheng Li, Ninghui Li
ADMA
2006
Springer
131views Data Mining» more  ADMA 2006»
16 years 1 months ago
Distance Guided Classification with Gene Expression Programming
Gene Expression Programming (GEP) aims at discovering essential rules hidden in observed data and expressing them mathematically. GEP has been proved to be a powerful tool for cons...
Lei Duan, Changjie Tang, Tianqing Zhang, Dagang We...
ICDM
2005
IEEE
128views Data Mining» more  ICDM 2005»
16 years 1 months ago
An Expected Utility Approach to Active Feature-Value Acquisition
In many classification tasks training data have missing feature values that can be acquired at a cost. For building accurate predictive models, acquiring all missing values is of...
Prem Melville, Foster J. Provost, Raymond J. Moone...