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» Identifying non-actionable association rules
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TASE
2008
IEEE
13 years 6 months ago
Automated Planning and Optimization of Lumber Production Using Machine Vision and Computed Tomography
An automated system for planning and optimization of lumber production using Machine Vision and Computed Tomography (CT) is proposed. Cross-sectional CT images of hardwood logs are...
Suchendra M. Bhandarkar, Xingzhi Luo, Richard F. D...
DIS
2006
Springer
13 years 10 months ago
Visual Interactive Subgroup Discovery with Numerical Properties of Interest
Abstract. We propose an approach to subgroup discovery using distribution rules (a kind of association rules with a probability distribution on the consequent) for numerical proper...
Alípio Mário Jorge, Fernando Pereira...
BMCBI
2008
101views more  BMCBI 2008»
13 years 6 months ago
Prediction of glycosylation sites using random forests
Background: Post translational modifications (PTMs) occur in the vast majority of proteins and are essential for function. Prediction of the sequence location of PTMs enhances the...
Stephen E. Hamby, Jonathan D. Hirst
BMCBI
2008
173views more  BMCBI 2008»
13 years 6 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
BMCBI
2010
240views more  BMCBI 2010»
13 years 6 months ago
TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs
Background: MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challe...
Ming Lu, Bing Shi, Juan Wang, Qun Cao, Qinghua Cui