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» Classes and clusters in data analysis
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JMLR
2006
136views more  JMLR 2006»
15 years 6 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence
ICML
2007
IEEE
16 years 7 months ago
Least squares linear discriminant analysis
Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
Jieping Ye
CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
15 years 8 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
PAMI
2008
162views more  PAMI 2008»
15 years 6 months ago
Bayes Optimality in Linear Discriminant Analysis
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
Onur C. Hamsici, Aleix M. Martínez
CCGRID
2005
IEEE
16 years 9 days ago
A grid-based system for microbial genome comparison and analysis
Genome comparison and analysis can reveal the structures and functions of genome sequences of different species. As more genomes are sequenced, genomic data sources are rapidly in...
Yudong Sun, Anil Wipat, Matthew R. Pocock, P. A. L...