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ICML
2005
IEEE
16 years 2 months ago
Ensembles of biased classifiers
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Andreas Heß, Nicholas Kushmerick, Rinat Khou...
ICML
2003
IEEE
16 years 2 months ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
ICML
2002
IEEE
16 years 2 months ago
Learning Decision Trees Using the Area Under the ROC Curve
ROC analysis is increasingly being recognised as an important tool for evaluation and comparison of classifiers when the operating characteristics (i.e. class distribution and cos...
César Ferri, José Hernández-O...
ICML
1997
IEEE
16 years 2 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman
ICML
1997
IEEE
16 years 2 months ago
Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Dale Schuurmans, Lyle H. Ungar, Dean P. Foster