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142
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BMCBI
2010
118views more  BMCBI 2010»
15 years 3 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...
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 5 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
113
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PKDD
2000
Springer
100views Data Mining» more  PKDD 2000»
15 years 7 months ago
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Previous algoritms for the construction of belief networks structures from data are mainly based either on independence criteria or on scoring metrics. The aim of this paper is to ...
Silvia Acid, Luis M. de Campos
ECML
2006
Springer
15 years 7 months ago
Fisher Kernels for Relational Data
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Uwe Dick, Kristian Kersting
ICML
2009
IEEE
16 years 4 months ago
Learning nonlinear dynamic models
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sh...
John Langford, Ruslan Salakhutdinov, Tong Zhang