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ICML
2003
IEEE
16 years 3 months ago
Weighted Order Statistic Classifiers with Large Rank-Order Margin
We investigate how stack filter function classes like weighted order statistics can be applied to classification problems. This leads to a new design criteria for linear classifie...
Reid B. Porter, Damian Eads, Don R. Hush, James Th...
148
Voted
ICML
2001
IEEE
16 years 3 months ago
Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation
This work is concerned with the estimation of a classifier's accuracy. We first review some existing methods for error estimation, focusing on cross-validation and bootstrap,...
Gregory Shakhnarovich, Ran El-Yaniv, Yoram Baram
142
Voted
AMFG
2005
IEEE
293views Biometrics» more  AMFG 2005»
15 years 8 months ago
How to Train a Classifier Based on the Huge Face Database?
The development of web and digital camera nowadays has made it easier to collect more than hundreds of thousands of examples. How to train a face detector based on the collected en...
Jie Chen, Ruiping Wang, Shengye Yan, Shiguang Shan...
111
Voted
ECML
2007
Springer
15 years 6 months ago
On Pairwise Naive Bayes Classifiers
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can...
Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyk...
131
Voted
KDD
1995
ACM
109views Data Mining» more  KDD 1995»
15 years 6 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani