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www.eeworm.com/read/251838/4414808
m tabular_chance_node.m
function CPD = tabular_chance_node(sz, CPT)
% TABULAR_CHANCE_NODE Like tabular_CPD, but simplified
% CPD = tabular_chance_node(sz, CPT)
%
% sz(1:end-1) is the sizes of the parents, sz(end) is the size
www.eeworm.com/read/251838/4414912
m log_prob_node.m
function L = log_prob_node(CPD, self_ev, pev)
% LOG_PROB_NODE Compute sum_m log P(x(i,m)| x(pi_i,m), theta_i) for node i (discrete)
% L = log_prob_node(CPD, self_ev, pev)
%
% self_ev(m) is the evidenc
www.eeworm.com/read/251838/4414938
m log_prob_node.m
function L = log_prob_node(CPD, self_ev, pev)
% LOG_PROB_NODE Compute prod_m log P(x(i,m)| x(pi_i,m), theta_i) for node i (root)
% L = log_prob_node(CPD, self_ev, pev)
%
% self_ev{m} is the evidence o
www.eeworm.com/read/251838/4414952
m tabular_decision_node.m
function CPD = tabular_decision_node(sz, CPT)
% TABULAR_DECISION_NODE Represent the randomized policy over a discrete decision/action node as a table
% CPD = tabular_decision_node(sz, CPT)
%
% sz(1:en
www.eeworm.com/read/251838/4414958
m tabular_decision_node.m
function CPD = tabular_decision_node(bnet, self, CPT)
% TABULAR_DECISION_NODE Represent a stochastic policy over a discrete decision/action node as a table
% CPD = tabular_decision_node(bnet, self, CP
www.eeworm.com/read/251522/4418806
m scg_3node.m
% This example is from Page.143 of "Probabilistic Networks and Expert Systems",
% Cowell, Dawid, Lauritzen and Spiegelhalter, 1999, Springer.
X = 1; Y = 2; Z = 3;
n = 3;
dag = zeros(n);
dag(X, Y)=1;
www.eeworm.com/read/251522/4418949
m log_prob_node.m
function L = log_prob_node(CPD, self_ev, pev)
% LOG_PROB_NODE Compute prod_m log P(x(i,m)| x(pi_i,m), theta_i) for node i (gaussian)
% L = log_prob_node(CPD, self_ev, pev)
%
% self_ev(m) is the eviden
www.eeworm.com/read/251522/4418960
m tabular_chance_node.m
function CPD = tabular_chance_node(sz, CPT)
% TABULAR_CHANCE_NODE Like tabular_CPD, but simplified
% CPD = tabular_chance_node(sz, CPT)
%
% sz(1:end-1) is the sizes of the parents, sz(end) is the size
www.eeworm.com/read/251522/4418980
m tabular_decision_node.m
function CPD = tabular_decision_node(sz, CPT)
% TABULAR_DECISION_NODE Represent the randomized policy over a discrete decision/action node as a table
% CPD = tabular_decision_node(sz, CPT)
%
% sz(1:en
www.eeworm.com/read/242733/4536384
cpp node2d.cpp
/*
Copyright (c) 1995-2000 Microsoft Corporation. All rights reserved.
*/
#include "precomp.h"
Node2D::Node2D(
int width,
int height,
int x,
int y,
int align, // = 4
Node2D