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BMCBI
2010
224views more  BMCBI 2010»
13 years 6 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
BMCBI
2006
94views more  BMCBI 2006»
13 years 6 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
BMCBI
2004
133views more  BMCBI 2004»
13 years 6 months ago
Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction m
Background: Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have pre...
Yasuyuki Tomita, Shuta Tomida, Yuko Hasegawa, Yoic...
ICIC
2007
Springer
14 years 7 days ago
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal...
Huanhuan Chen, Xin Yao
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
13 years 11 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...