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c sis1.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c tms2.c

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c sis2.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c sis1.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c tms2.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c sis2.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c tms1.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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c tms1.c

/************************************************************************* (c) Copyright 1993 University of Tennessee All R
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m multilogit.m

function results = multilogit(y,x,beta0,maxit,tol); % PURPOSE: implements multinomial logistic regression % Pr(y_i=j) = exp(x_i'beta_j)/sum_l[exp(x_i'beta_l)] % where: % i = 1,2,...,nobs
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m ksvdd.m

%KSVDD Support Vector Data Description on general kernel matrix % % W = KSVDD(X,FRACERR,WK) % % Train an SVDD on the data X, which is first mapped by mapping WK % (see for possibilities myproxm
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