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» Making generative classifiers robust to selection bias
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KDD
2007
ACM
139views Data Mining» more  KDD 2007»
11 years 5 days ago
Making generative classifiers robust to selection bias
Andrew T. Smith, Charles Elkan
ICML
2004
IEEE
11 years 17 days ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
10 years 1 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
ICML
2009
IEEE
11 years 17 days ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...
ESANN
2008
10 years 1 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...
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