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» GRASP for Instance Selection in Medical Data Sets
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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
14 years 10 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
CIDM
2009
IEEE
15 years 4 months ago
Diversity analysis on imbalanced data sets by using ensemble models
— 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...
Shuo Wang, Xin Yao
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
15 years 3 months ago
Exploring medical data using visual spaces with genetic programming and implicit functional mappings
Two medical data sets (Breast cancer and Colon cancer) are investigated within a visual data mining paradigm through the unsupervised construction of virtual reality spaces using ...
Julio J. Valdés, Robert Orchard, Alan J. Ba...
ICASSP
2008
IEEE
15 years 4 months ago
Detecting mild cognitive loss with continuous monitoring of medication adherence
This paper describes an approach for detecting early cognitive loss using medication adherence behavior. We investigate the discriminative power of a comprehensive set of recurren...
Yonghong Huang, Deniz Erdogmus, Zhengdong Lu, Todd...
LREC
2010
176views Education» more  LREC 2010»
14 years 11 months ago
There's no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
Ines Rehbein, Josef Ruppenhofer