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CIDM
2009
IEEE
13 years 11 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
NCA
2006
IEEE
13 years 4 months ago
Analysing the localisation sites of proteins through neural networks ensembles
Scientists involved in the area of proteomics are currently seeking integrated, customised and validated research solutions to better expedite their work in proteomics analyses and...
Aristoklis D. Anastasiadis, George D. Magoulas
AUSAI
2009
Springer
13 years 8 months ago
Ensemble Approach for the Classification of Imbalanced Data
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
SIGKDD
2008
150views more  SIGKDD 2008»
13 years 4 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
13 years 2 months ago
Ensemble-Vis: A Framework for the Statistical Visualization of Ensemble Data
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...