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ICML
2007
IEEE
14 years 6 months ago
Discriminative Gaussian process latent variable model for classification
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Raquel Urtasun, Trevor Darrell
NECO
2000
190views more  NECO 2000»
13 years 5 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar
CSDA
2006
96views more  CSDA 2006»
13 years 5 months ago
Analysis of new variable selection methods for discriminant analysis
Several methods to select variables that are subsequently used in discriminant analysis are proposed and analysed. The aim is to find from among a set of m variables a smaller sub...
Joaquín A. Pacheco, Silvia Casado, Laura N&...
BMCBI
2010
135views more  BMCBI 2010»
13 years 5 months ago
A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis
Background: Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query seq...
Ji Woong Kim, Yongju Ahn, Kichan Lee, Sung-Hee Par...
ESANN
2006
13 years 6 months ago
Using distributed genetic programming to evolve classifiers for a brain computer interface
The objective of this paper is to illustrate the application of genetic programming to evolve classifiers for multi-channel time series data. The paper shows how high performance d...
Eva Alfaro-Cid, Anna Esparcia-Alcázar, Ken ...