www.gusucode.com > classification_matlab_toolbox分类方法工具箱源码程序 > code/Classification_toolbox/ML.m
function D = ML(train_features, train_targets, AlgorithmParameters, region) % Classify using the maximum-likelyhood algorithm % Inputs: % features - Train features % targets - Train targets % Dummy - Unused % region - Decision region vector: [-x x -y y number_of_points] % % Outputs % D - Decision sufrace train_one = find(train_targets == 1); train_zero = find(train_targets == 0); %Estimate mean and covariance for class 0 param_struct.m0 = mean(train_features(:,train_zero)'); param_struct.s0 = cov(train_features(:,train_zero)',1); param_struct.p0 = length(train_zero)/length(train_targets); %Estimate mean and covariance for class 1 param_struct.m1 = mean(train_features(:,train_one)'); param_struct.s1 = cov(train_features(:,train_one)',1); param_struct.w0 = 1; param_struct.w1 = 1; %Find decision region D = decision_region(param_struct, region);