7 search results - page 1 / 2 » Online learning with minority class resampling |
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
This paper considers using online binary classification for target detection where the goal is to identify signals of interest within a sequence of received signals generated by ...
RSCTC
2010
Springer
13 years 2 months ago
2010
Springer
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of ...
IEAAIE
2010
Springer
13 years 2 months ago
2010
Springer
The present paper studies the influence of two distinct factors on the performance of some resampling strategies for handling imbalanced data sets. In particular, we focus on the n...
ISCI
2008
13 years 4 months ago
2008
In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the clas...
CIDM
2009
IEEE
13 years 11 months ago
2009
IEEE
— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...