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» Efficient Kernel-based Learning for Trees
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FLAIRS
2006
14 years 10 months ago
Generalized Entropy for Splitting on Numerical Attributes in Decision Trees
Decision Trees are well known for their training efficiency and their interpretable knowledge representation. They apply a greedy search and a divide-and-conquer approach to learn...
Mingyu Zhong, Michael Georgiopoulos, Georgios C. A...
NIPS
2001
14 years 10 months ago
Thin Junction Trees
We present an algorithm that induces a class of models with thin junction trees--models that are characterized by an upper bound on the size of the maximal cliques of their triang...
Francis R. Bach, Michael I. Jordan
ICML
2006
IEEE
15 years 10 months ago
Fast particle smoothing: if I had a million particles
We propose efficient particle smoothing methods for generalized state-spaces models. Particle smoothing is an expensive O(N2 ) algorithm, where N is the number of particles. We ov...
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud ...
BMCBI
2010
109views more  BMCBI 2010»
14 years 9 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...
JMLR
2008
169views more  JMLR 2008»
14 years 9 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen