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nan_train_lda_sparse

Linear Discriminant Analysis for the Small Sample Size Problem as described in

Calling Sequence

[CC] = nan_train_lda_sparse(X,G,par,tol)

Parameters

Input:

X :

(sparse) training data Xmat

G :

group coding Xmat of the training data

test :

(sparse) test data Xmat

Gtest :

group coding Xmat of the test data

par :

if par = 0 then classification exploits sparsity too

tol :

tolerance to distinguish zero eigenvalues

Output:

err :

Wrong classification rate (in %)

trafo :

LDA transformation vectors

Description

Algorithm 1 of J. Duintjer Tebbens, P. Schlesinger: 'Improving Implementation of Linear Discriminant Analysis for the High Dimension/Small Sample Size Problem', Computational Statistics and Data Analysis, vol. 52, no. 1, pp. 423-437, 2007.

Bibliography

J. Duintjer Tebbens, P. Schlesinger: 'Improving

Implementation of Linear Discriminant Analysis for the High Dimension/Small Sample Size

Problem', Computational Statistics and Data Analysis, vol. 52, no. 1,

pp. 423-437, 2007.

Authors

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