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% Chapter 05: Example-5.17: Overlap and save % n = 0:9; x = n+1; Lenx = length(x); h = [1,0,-1]; M = 3; M1 = M-1; L = N-M1; N = 6; h = [h zeros(1,N-M)]; % x = [zeros(1,M1), x, zeros(1,N-1)]; K

%LPBALL_DIST Compute Lp distance to a mean % % [F,G,H] = LPBALL_DIST(M,X,P,FRAC) % % Compute the maximum distance of objects X to the mean M, using Lp % distances with P. To make the distance a bi

%IS_OCSET True for one-class datasets % % is_ocset(a) returns true if the dataset a is a one-class dataset, % containing only classes 'target' and/or 'outlier'. % Copyright: D.M.J. Tax, D.M.J.Ta

% Show how several one-class classifiers can be combined. % To make the classifier outputs comparable, the outputs should be % normalized using dd_normc % Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org

function y=cirshftt(x,m,N) %[y]=cirshftt(x,m,N) %----------------------- % if length(x)>N error('N

function [y]=ovrlpsav(x,h,N) %[y]=ovrlpsav(x,h,N) %------------------- % Lenx=length(x); M=length(h); M1=M-1;L=N-M1; h=[h,zeros(1,N-M)]; x=[zeros(1,M1),x,zeros(1,N-1)]; K=floor((Lenx+M1-1)/

int maxsum(int m) { int al; //al=al-1; int b[al+1],c[al+1]; b[0]=0,c[0]=0; for(int i=1;i

%LPBALL_DIST Compute Lp distance to a mean % % [F,G,H] = LPBALL_DIST(M,X,P,FRAC) % % Compute the maximum distance of objects X to the mean M, using Lp % distances with P. To make the distance a bi

%IS_OCSET True for one-class datasets % % is_ocset(a) returns true if the dataset a is a one-class dataset, % containing only classes 'target' and/or 'outlier'. % Copyright: D.M.J. Tax, D.M.J.Ta

% Show how several one-class classifiers can be combined. % To make the classifier outputs comparable, the outputs should be % normalized using dd_normc % Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org