matlab fisher score,用于特征选择的方法.zip

function [out] = fsFisher(X,Y) %Fisher Score, use the N var formulation % X, the data, each raw is an instance % Y, the label in 1 2 3 ... format numC = max(Y); [~, numF] = size(X); out.W = zeros(1,numF); % statistic for classes cIDX = cell(numC,1); n_i = zeros(numC,1); for j = 1:numC cIDX{j} = find(Y(:)==j); n_i(j) = length(cIDX{j}); end % calculate score for each features for i = 1:numF temp1 = 0; temp2 = 0; f_i = X(:,i); u_i = mean(f_i); for j = 1:numC u_cj = mean(f_i(cIDX{j})); var_cj = var(f_i(cIDX{j}),1); temp1 = temp1 + n_i(j) * (u_cj-u_i)^2; temp2 = temp2 + n_i(j) * var_cj; end if temp1 == 0 out.W(i) = 0; else if temp2 == 0 out.W(i) = 100; else out.W(i) = temp1/temp2; end end end [~, out.fList] = sort(out.W, 'descend'); out.prf = 1;