代码搜索：evaluate

找到约 3,619 项符合「evaluate」的源代码

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www.eeworm.com/read/166306/10024537

m fquad.m

function[val,g] = fquad(x,c,H,mtxmpy,data,D) %FQUAD Evaluate quadratic function. % val = FQUAD(x,c,H,mtxmpy,data,D) evaluates the quadratic % function val = c'*x + .5*x'*D*MTX*D*x, where % D i
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www.eeworm.com/read/164422/10108696

m mixgauss_prob.m

function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm) % EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians % function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma,
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www.eeworm.com/read/164422/10108761

m matrix_t_pdf.m

function p = matrix_T_pdf(A, M, V, K, n) % MATRIX_T_PDF Evaluate the density of a matrix under a Matrix-T distribution % p = matrix_T_pdf(A, M, V, K, n) % See "Bayesian Linear Regression", T. Minka,
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www.eeworm.com/read/358694/10181664

m fquad.m

function[val,g] = fquad(x,c,H,mtxmpy,data,D) %FQUAD Evaluate quadratic function. % val = FQUAD(x,c,H,mtxmpy,data,D) evaluates the quadratic % function val = c'*x + .5*x'*D*MTX*D*x, where % D i
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www.eeworm.com/read/425546/10348663

m matrix_t_pdf.m

function p = matrix_T_pdf(A, M, V, K, n) % MATRIX_T_PDF Evaluate the density of a matrix under a Matrix-T distribution % p = matrix_T_pdf(A, M, V, K, n) % See "Bayesian Linear Regression", T. Min
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www.eeworm.com/read/353896/10407040

m fquad.m

function[val,g] = fquad(x,c,H,mtxmpy,data,D) %FQUAD Evaluate quadratic function. % val = FQUAD(x,c,H,mtxmpy,data,D) evaluates the quadratic % function val = c'*x + .5*x'*D*MTX*D*x, where % D i
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www.eeworm.com/read/349646/10808464

m mixgauss_prob.m

function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm) % EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians % function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma
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www.eeworm.com/read/349646/10808504

m matrix_t_pdf.m

function p = matrix_T_pdf(A, M, V, K, n) % MATRIX_T_PDF Evaluate the density of a matrix under a Matrix-T distribution % p = matrix_T_pdf(A, M, V, K, n) % See "Bayesian Linear Regression", T. Min
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www.eeworm.com/read/349646/10809022

m mixgauss_prob.m

function [B, B2] = mixgauss_prob(data, mu, Sigma, mixmat, unit_norm) % EVAL_PDF_COND_MOG Evaluate the pdf of a conditional mixture of Gaussians % function [B, B2] = eval_pdf_cond_mog(data, mu, Sigma
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www.eeworm.com/read/349646/10809164

m matrix_t_pdf.m

function p = matrix_T_pdf(A, M, V, K, n) % MATRIX_T_PDF Evaluate the density of a matrix under a Matrix-T distribution % p = matrix_T_pdf(A, M, V, K, n) % See "Bayesian Linear Regression", T. Min
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