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» Using Derivation Trees for Treebank Error Detection
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BMCBI
2004
139views more  BMCBI 2004»
13 years 8 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend
ECML
2006
Springer
14 years 4 days ago
Cost-Sensitive Decision Tree Learning for Forensic Classification
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
TOOLS
2008
IEEE
14 years 2 months ago
Towards Raising the Failure of Unit Tests to the Level of Compiler-Reported Errors
Running unit tests suites with contemporary tools such as JUNIT can show the presence of bugs, but not their locations. This is different from checking a program with a compiler, w...
Friedrich Steimann, Thomas Eichstädt-Engelen,...
BMCBI
2008
219views more  BMCBI 2008»
13 years 8 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
CEC
2010
IEEE
13 years 9 months ago
Evolving cascades of voting feature detectors for vehicle detection in satellite imagery
We propose an evolutionary method for detection of vehicles in satellite imagery which involves a large number of simple elementary features and multiple detectors trained by genet...
Krzysztof Krawiec, Bartosz Kukawka, Tomasz Macieje...