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» Robust bounds for classification via selective sampling
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BMCBI
2008
186views more  BMCBI 2008»
14 years 11 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
LREC
2010
176views Education» more  LREC 2010»
15 years 1 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
ICIAR
2004
Springer
15 years 5 months ago
Learning an Information Theoretic Transform for Object Detection
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Jianzhong Fang, Guoping Qiu
BMCBI
2010
224views more  BMCBI 2010»
14 years 11 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
IJBRA
2007
97views more  IJBRA 2007»
14 years 11 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...