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» Improving data mining utility with projective sampling
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PAKDD
2010
ACM
134views Data Mining» more  PAKDD 2010»
14 years 11 months ago
Generating Diverse Ensembles to Counter the Problem of Class Imbalance
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
T. Ryan Hoens, Nitesh V. Chawla
KDD
1999
ACM
152views Data Mining» more  KDD 1999»
15 years 1 months ago
Applying General Bayesian Techniques to Improve TAN Induction
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
Jesús Cerquides
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
15 years 4 months ago
Projective Clustering Ensembles
Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consi...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
CG
2008
Springer
14 years 9 months ago
Masked photo blending: Mapping dense photographic data set on high-resolution sampled 3D models
The technological advance of sensors is producing an exponential size growth of the data coming from 3D scanning and digital photography. The production of digital 3D models consi...
Marco Callieri, Paolo Cignoni, Massimiliano Corsin...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
14 years 11 months ago
Roughly Balanced Bagging for Imbalanced Data
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
Shohei Hido, Hisashi Kashima