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/215485/4903549

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/197905/5090995

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/346158/3189581

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/292984/3935821

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/292964/3936969

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/434858/1867993

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/393163/2487916

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/160391/5571237

m mhmm1.m

% Make an HMM with mixture of Gaussian observations % Q1 ---> Q2 % / | / | % M1 | M2 | % \ v \ v % Y1 Y2 % where Pr(m=j|q=i) is a multinomial and Pr(y|m,q) is a Gaussian
www.eeworm.com/read/373627/9445733

html multinom.html

R: Fit Multinomial Log-linear Models
www.eeworm.com/read/449504/7502210

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