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MCS
2010
Springer
14 years 1 months ago
Online Non-stationary Boosting
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
CCE
2005
13 years 8 months ago
Selecting maximally informative genes
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...
Ioannis P. Androulakis
AI
2009
Springer
14 years 2 months ago
Cost-Based Sampling of Individual Instances
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
William Klement, Peter A. Flach, Nathalie Japkowic...
JMLR
2002
144views more  JMLR 2002»
13 years 8 months ago
Round Robin Classification
In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...
Johannes Fürnkranz
TNN
2010
127views Management» more  TNN 2010»
13 years 3 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia