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文件名称:lda_test
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- 上传时间:2013-07-09
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文件大小:1.29kb
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Function to implement Linear Discriminant Analysis
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values- Function to implement Linear Discriminant Analysis
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values- Function to implement Linear Discriminant Analysis
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values
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lda_test.m
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