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» Is an ordinal class structure useful in classifier learning
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BMCBI
2010
118views more  BMCBI 2010»
13 years 9 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
BMCBI
2004
190views more  BMCBI 2004»
13 years 8 months ago
RAG: RNA-As-Graphs web resource
Background: The proliferation of structural and functional studies of RNA has revealed an increasing range of RNA's structural repertoire. Toward the objective of systematic ...
Daniela Fera, Namhee Kim, Nahum Shiffeldrim, Julie...
ICFHR
2010
214views Biometrics» more  ICFHR 2010»
13 years 3 months ago
Special Radical Detection by Statistical Classification for On-line Handwritten Chinese Character Recognition
The hierarchical nature of Chinese characters has inspired radical-based recognition, but radical segmentation from characters remains a challenge. We previously proposed a radica...
Long-Long Ma, Adrien Delaye, Cheng-Lin Liu
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 9 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
BMCBI
2010
179views more  BMCBI 2010»
13 years 9 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...