wehub-resource-sync
21 lines
586 B
Matlab
Executable File
21 lines
586 B
Matlab
Executable File
function y = nbGaussPred(model, X)
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% Prediction of naive Bayes classifier with independent Gaussian.
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% input:
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% model: trained model structure
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% X: d x n data matrix
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% output:
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% y: 1 x n predicted class label
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% Written by Mo Chen (sth4nth@gmail.com).
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mu = model.mu;
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var = model.var;
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w = model.w;
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assert(all(size(mu)==size(var)));
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d = size(mu,1);
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lambda = 1./var;
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ml = mu.*lambda;
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M = bsxfun(@plus,lambda'*X.^2-2*ml'*X,dot(mu,ml,1)'); % M distance
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c = d*log(2*pi)+2*sum(log(var),1)'; % normalization constant
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R = -0.5*bsxfun(@plus,M,c);
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[~,y] = max(bsxfun(@times,exp(R),w),[],1);
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