代码搜索：Multinomial
找到约 224 项符合「Multinomial」的源代码
代码结果 224
www.eeworm.com/read/296847/8075037
m nmf_prob.m
function [W,H]=nmfprob(X,K,maxiter,speak)
%
% Probabilistic NFM interpretating X as samples from a multinomial
%
% INPUT:
% X (N,M) : N (dimensionallity) x M (samples) non negative input matrix
www.eeworm.com/read/449504/7502140
m mlogit.m
function results = mlogit(y,x,beta,theta)
% PURPOSE: multinomial logistic regression
% logit(p_ij) = theta(j) + x_i'beta , i = 1,..,nobs, j = 1,..,k-1,
%-------------------------------------------
www.eeworm.com/read/440842/7680277
m mlogit.m
function results = mlogit(y,x,beta,theta)
% PURPOSE: multinomial logistic regression
% logit(p_ij) = theta(j) + x_i'beta , i = 1,..,nobs, j = 1,..,k-1,
%-------------------------------------------
www.eeworm.com/read/436945/7758468
m softmax.m
function [f, iter, dev, hess] = softmax(X, k, prior, varargin)
%SOFTMAX Multinomial feed-forward neural-network
% F = SOFTMAX(X, K, PRIOR) returns a SOFTMAX object containing the
% weights of a fe
www.eeworm.com/read/296712/8080655
cpp 多项式.cpp
#include
using namespace std;
struct XPower{
int cof;//系数coefficient
int power;//幂数
XPower* next;
};
typedef XPower* link;
class XPowerMult{//多项式multinomial
private:
link head;
www.eeworm.com/read/328078/13047159
m softmax.m
function [f, iter, dev, hess] = softmax(X, k, prior, varargin)
%SOFTMAX Multinomial feed-forward neural-network
% F = SOFTMAX(X, K, PRIOR) returns a SOFTMAX object containing the
% weights of a fe
www.eeworm.com/read/492929/6414184
m mlogit.m
function results = mlogit(y,x,beta,theta)
% PURPOSE: multinomial logistic regression
% logit(p_ij) = theta(j) + x_i'beta , i = 1,..,nobs, j = 1,..,k-1,
%-------------------------------------------
www.eeworm.com/read/152250/12130874
m entropic_map_estimate.m
function [theta, loglik] = entropic_map_estimate(counts, Z)
% ENTROPIC_MAP_ESTIMATE Find MAP estimate of multinomial using entropic prior
% [theta, loglik] = entropic_map_estimate(counts, Z)
%
% The e
www.eeworm.com/read/152250/12130884
m my_entropic_map.m
function [theta, loglik] = my_entropic_map(counts, Z)
% ENTROPIC_MAP_ESTIMATE Find MAP estimate of multinomial using entropic prior
% [theta, loglik] = entropic_map_estimate(counts, Z)
%
% The entropi
www.eeworm.com/read/152250/12130920
m entropic_map_estimate1.m
function [theta, loglik] = entropic_map_estimate(counts, Z)
% ENTROPIC_MAP_ESTIMATE Find MAP estimate of multinomial using entropic prior
% [theta, loglik] = entropic_map_estimate(counts, Z)
%
% The e