代码搜索：Bayesian

找到约 1,632 项符合「Bayesian」的源代码

代码结果 1,632
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m bayescls.m

function [y, dfce] = bayescls( X, model ) % BAYESCLS Bayesian classifier with reject option. % % Synopsis: % [y, dfce] = bayescls(X,model) % % Description: % This function implements the classifier
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www.eeworm.com/read/183855/9134568

c new_neighbor.c

/*----------------------------------------------------- PROGRAM : new_neighbor.c DATE : 6/15/94 AUTHOR : Wasiuddin Wahid, wasi@media.mit.edu NOTE : Baback added Bayesian Similarity
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www.eeworm.com/read/183855/9134602

c neighbor.c

/*----------------------------------------------------- PROGRAM : neighbor.c DATE : 6/15/94 AUTHOR : Wasiuddin Wahid, wasi@media.mit.edu NOTE : Baback added Bayesian Similarity Metr
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www.eeworm.com/read/362246/10009282

m bayescls.m

function [y, dfce] = bayescls( X, model ) % BAYESCLS Bayesian classifier with reject option. % % Synopsis: % [y, dfce] = bayescls(X,model) % % Description: % This function implements the classifier
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www.eeworm.com/read/280595/10310568

m bayescls.m

function [y, dfce] = bayescls( X, model ) % BAYESCLS Bayesian classifier with reject option. % % Synopsis: % [y, dfce] = bayescls(X,model) % % Description: % This function implements the classifier
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www.eeworm.com/read/162188/10327605

src maxbayes.src

/* ** maxbayes.src MAXBAYES - Bayesian Inference from Weighted ** Likelihood Bootstrap Likelihood Bootstrap ** ** ** (C) Copyright 1995-1996 Aptech Systems, Inc. ** All
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www.eeworm.com/read/449504/7503084

m sar_gv.m

function results = sar_gv(y,x,W,ndraw,nomit,prior) % PURPOSE: Bayesian estimates of the spatial autoregressive model % THIS FUNCTION: estimates the heteroscedasticity parameter r % a
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www.eeworm.com/read/299459/7849032

m bayescls.m

function [y, dfce] = bayescls( X, model ) % BAYESCLS Bayesian classifier with reject option. % % Synopsis: % [y, dfce] = bayescls(X,model) % % Description: % This function implements the classifier
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www.eeworm.com/read/196932/8040053

m bcmtrain.m

function net = bcmtrain(net,method,alg,options) % bcmtrain - Kernel parameter optimization for Bayesian Committee Machine % % Synopsis: % net = bcmtrain(net,method,alg,options) % % Arguments: %
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www.eeworm.com/read/196932/8040063

m bcm.m

function net = bcm(gpnet) % bcm - Bayesian Committee Machine % % Synopsis: % net = bcm(gpnet) % % Arguments: % gpnet: A Gaussian process template for BCM modules, as output by Netlab's %
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