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LpNPSVM

A Matlab code for robust nonparallel proximal support vector machine with Lp-norm regularization. (You could Right-Click [Code] , and Save, then you can download the whole matlab code.)


Reference

Xiao-Quan Sun, Yi-Jian Chen, Yuan-Hai Shao, Chun-Na Li*, Chang-Hui Wang. Robust nonparallel proximal support vector machine with Lp-norm regularization.


Main Function
function [w1, w2, b1, b2, iter] = LpNPSVM(Atrain,Btrain,delta,p,w0,itmax,epsmax) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % LpNPSVM: % Robust nonparallel proximal support vector machine with Lp-norm regularization % [w1, b1, w2, b2] = LpNPSVM(Atrain,Btrain,FunPara,w0,itmax,epsmax) % Input: % Atrain: Positive class data matrix. Each row vector of Atrain is a data point. % Btrain: Positive class data matrix. Each row vector of Btrain is a data point. % delta: regularization term parameter. % FunPara: parameters % FunPara.delta: regularization parameter % FunPara.p: p in Lp-norm regularization term % w0: Initial hyperplane direction and bias % itmax: Maximun iteration number % epsmax: Tolerance % % % % % Eample: % Atrain = rand(30,2); % Btrain = rand(30,2) + 1; % w0 = ones(1,size(Atrain,2) + 1); % Initialization % FunPara.p = 1.5; % FunPara.delta = 0.05; % [w1, b1, w2, b2] = LpNPSVM(Atrain,Btrain,FunPara); % Reference: % Robust nonparallel proximal support vector machine with Lp-norm regularization. % IEEE Access, 2018, 6: 20334-20347. % Xiao-Quan Sun, Yi-Jian Chen, Yuan-Hai Shao, Chun-Na Li*, Chang-Hui Wang % Version 2.0 --June/2018 % Written by Chun-Na Li (na1013na@163.com) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Initailization %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if nargin == 2 FunPara.delta = 0.05; FunPara.p = 1.5; w0 = ones(size(Atrain,2) + 1,1); itmax = 100; epsmax = 10^(-5); elseif nargin == 3 w0 = ones(size(Atrain,2) + 1,1); itmax = 100; epsmax = 10^(-5); elseif nargin == 4 itmax = 100; epsmax = 10^(-5); elseif nargin == 5 epsmax = 10^(-5); end delta = FunPara.delta; p = FunPara.p; [nSmpA, nFea] = size(Atrain); [nSmpB, ~] = size(Btrain); wp0 = w0; wn0 = w0; epsWX = 10^-4; epsW = 10^-4; Atrainbar = [Atrain,ones(size(Atrain,1),1)]'; Btrainbar = [Btrain,ones(size(Btrain,1),1)]'; while 1 %%%%%%%%%%%%%%%%%% % % % For A %%%%%%%%%%%%%%%%%% Ht_A = zeros(nFea+1, nFea+1); ht_A = zeros(nFea+1,1); for i = 1:nSmpA Atrainbari = Atrainbar(:,i); Ht_A = Ht_A + (Atrainbari*Atrainbari')/abs(wp0'*Atrainbari + epsWX); end for i = 1:nSmpB ht_A = ht_A + sign(wp0'*Btrainbar(:,i))*Btrainbar(:,i); end q_A = (abs(wp0) + epsW).^(p - 2); Ht_Ar = delta*diag(q_A); Ht_A = Ht_A + Ht_Ar; wp = (Ht_A\ht_A)/(ht_A'*inv(Ht_A)*ht_A); wp0 = wp; %%%%%%%%%%%%%%%%%% % % % For B %%%%%%%%%%%%%%%%%% Ht_B = zeros(nFea+1, nFea+1); ht_B = zeros(nFea+1,1); for i = 1:nSmpB Btrainbari = Btrainbar(:,i); Ht_B = Ht_B + (Btrainbari*Btrainbari')/abs(wp0'*Btrainbari + epsWX); end for i = 1:nSmpA ht_B = ht_B + sign(wn0'*Atrainbar(:,i))*Atrainbar(:,i); end q_B = (abs(wn0) + epsW).^(p - 2); Ht_Br = delta*diag(q_B); Ht_B = Ht_B + Ht_Br; wn = (Ht_B\ht_B)/(ht_B'*inv(Ht_B)*ht_B); wn0 = wn; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if max(abs(wp-wp0))itmax break; end end w1 = wp(1:length(wp)-1); b1 = wp(length(wp)); w2 = wn(1:length(wn)-1); b2 = wn(length(wn));
Contacts

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