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BMCBI
2008
186views more  BMCBI 2008»
14 years 9 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
IEAAIE
2004
Springer
15 years 2 months ago
Data Mining Approach for Analyzing Call Center Performance
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classifi...
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin...
PAMI
1998
127views more  PAMI 1998»
14 years 9 months ago
The Random Subspace Method for Constructing Decision Forests
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Tin Kam Ho
KDD
2001
ACM
359views Data Mining» more  KDD 2001»
15 years 9 months ago
Data mining techniques to improve forecast accuracy in airline business
Predictive models developed by applying Data Mining techniques are used to improve forecasting accuracy in the airline business. In order to maximize the revenue on a flight, the ...
Christoph Hueglin, Francesco Vannotti
JCST
2010
109views more  JCST 2010»
14 years 4 months ago
The Inverse Classification Problem
In this paper, we examine an emerging variation of the classification problem, which is known as the inverse classification problem. In this problem, we determine the features to b...
Charu C. Aggarwal, Chen Chen, Jiawei Han