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Author: niravnb

Bayesian Classifier/Linearly separable data/18_ls.txt

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+function [ A,B,C ] = case3par(m,c,m1,c1 )
+%Returns Parameters A,B & C which would be of form X'AX + B'X + C = 0 for
+%calculating decision boundary 
+
+A = -1/2*(inv(c) - inv(c1));
+B = inv(c)*m - inv(c1)*m1;
+C = -1/2*((m'*inv(c)*m) - (m1'*inv(c1)*m1)) - 1/2*log(det(c)/det(c1));
+
+
+end
+

Bayesian Classifier/Linearly separable data/case3par.m

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+% using addpath(genpath('/Users/NiravMBA/Desktop/IIT Madras/Semester I/Pattern Recognition/Assignment/Assignment 2/bosaris_toolkit'))
+
+function [] = demo_main(target,nontarget,target1,nontarget1,target2,nontarget2,target3,nontarget3,target4,nontarget4,caseno)
+% To plot DET Curve
+
+close all;
+
+fprintf('You need to run this script in Matlab''s graphical mode to see the plots.\n');
+
+% calculate an effective prior from target prior, Cmiss, and Cfa
+prior = effective_prior(0.33,1,1);
+
+
+%% Assign Target and Non Target Scores
+
+
+test_data.tar1 = target;
+test_data.non1 = nontarget;
+
+test_data.tar2 = target1;
+test_data.non2 = nontarget1;
+
+test_data.tar3 = target2;
+test_data.non3 = nontarget2;
+
+test_data.tar4 = target3;
+test_data.non4 = nontarget3;
+
+test_data.tar5 = target4;
+test_data.non5 = nontarget4;
+
+
+%% make a DET plot for all the five cases.
+demo_plot_det_for_fusion(test_data,prior,caseno);
+
+end

Bayesian Classifier/Linearly separable data/demo_main.m

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+function [ A,B,C ] = disciminantFunction(m,c )
+%Returns Parameter A,B & C for decison boundary which is of form 
+%  X'AX + B'X + C = 0.
+
+A = -1/2*inv(c);
+B = inv(c)*m;
+C = -1/2*m'*inv(c)*m - 1/2*log(det(c));
+
+
+end
+

Bayesian Classifier/Linearly separable data/disciminantFunction.m

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+clc; clear all; close all
+
+%% Calling Bayesian Classifier function for all five cases
+
+% CaseNumber: 1 -- Bayes with Covariance same for all classes
+% 
+%             2 -- Bayes with Covariance different for all classes
+% 
+%             3 -- Naive Bayes with C = \sigma^2*I.
+% 
+%             4 -- Naive Bayes with C same for all classes.
+% 
+%             5 -- Naive Bayes with C different for all classes.
+
+
+[t,nt] = myBayesianClassifier(1);
+[t1,nt1] = myBayesianClassifier(2);
+[t2,nt2] =  myBayesianClassifier(3);
+[t3,nt3] = myBayesianClassifier(4);
+[t4,nt4] = myBayesianClassifier(5);
+ 
+%% Uncomment this to plot ROC
+% legend('Case 1','Case 2','Case 3','Case 4','Case 5')
+%  print('-djpeg','LS_ROC.jpg', '-r300');
+%  hold off
+
+
+%% Uncomment this to plot DET
+% demo_main(t,nt,t1,nt1,t2,nt2,t3,nt3,t4,nt4,1);
+%  print('-djpeg','LS_DET.jpg', '-r300');
+
+
+ close all