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» Experiments with random projections for machine learning
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BMCBI
2010
109views more  BMCBI 2010»
13 years 7 months ago
Predicting gene function using hierarchical multi-label decision tree ensembles
Background: S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challe...
Leander Schietgat, Celine Vens, Jan Struyf, Hendri...
PR
2007
129views more  PR 2007»
13 years 7 months ago
EROS: Ensemble rough subspaces
Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
Qinghua Hu, Daren Yu, Zongxia Xie, Xiaodong Li
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 4 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
KBSE
2007
IEEE
14 years 1 months ago
The business case for automated software engineering
Adoption of advanced automated SE (ASE) tools would be favored if a business case could be made that these tools are more valuable than alternate methods. In theory, software pred...
Tim Menzies, Oussama El-Rawas, Jairus Hihn, Martin...
EMNLP
2011
12 years 7 months ago
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...