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runRealMatComp.m
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%%************************************************************************
%% run matrix completion problems for real data sets.
%%
%% NNLS, version 0:
%% Copyright (c) 2009 by
%% Kim-Chuan Toh and Sangwoon Yun
%%************************************************************************
clear;
warning off
addpath('solver');
addpath('PROPACKmod');
addpath('MatCompData');
%%
for dataset = [6]
if (dataset == 1)
exfile = 'jester-data-1';
Dt = xlsread(exfile);
fname = 'jester-1';
elseif (dataset == 2)
exfile = 'jester-data-2';
Dt = xlsread(exfile);
fname = 'jester-2';
elseif (dataset == 3)
exfile = 'jester-data-3';
Dt = xlsread(exfile);
fname = 'jester-3';
elseif (dataset == 4)
%%
%% jester dataset
%%
exfile1 = 'jester-data-1';
Dt1 = xlsread(exfile1);
exfile2 = 'jester-data-2';
Dt2 = xlsread(exfile2);
exfile3 = 'jester-data-3';
Dt3 = xlsread(exfile3);
Dt = [Dt1;Dt2;Dt3];
fname = 'jester-all';
elseif (dataset == 5)
%%
%% MovieLens Dataset: 943x1682 (usersxmovies)
%%
tM = dlmread('u100K.data','');
M = spconvert(tM);
fname = 'moive-100K';
elseif (dataset == 6)
%%
%% MovieLens Dataset: 6040x3900 (usersxmovies)
%%
tM = dlmread('u1M.data','');
M = spconvert(tM);
fname = 'moive-1M';
elseif (dataset == 7)
%%
%% MovieLens Dataset: 71567x10681 (usersxmovies)
%%
tM = dlmread('u10M.data','');
M = spconvert(tM);
fname = 'moive-10M';
end
if (dataset <= 4)
%%
%% jester data set
%%
M = Dt(1:end,2:end);
[nr,nc] = size(M);
%%
%% make zero ratings slightly non-zero.
%%
[ii,jj] = find(M==0);
M = M + spconvert([ii,jj,1e-8*ones(length(ii),1);nr,nc,0]);
%%
%% set non-rated entries (currently equal to 99) to 0.
%%
[ii,jj] = find(M==99);
M = M - spconvert([ii,jj,99*ones(length(ii),1); nr,nc,0]);
%%
NumPerRow = 10;
Msub = zeros(nr,nc);
for i=1:nr
rand('state',i);
Mrow = M(i,:);
truerow = find( abs(Mrow) > 1e-13 );
len = length(truerow);
rp = randperm(len);
chrow = truerow(rp(1:min(NumPerRow,len)));
Msub(i,chrow) = Mrow(chrow);
end
colnorm = sum(Msub.*Msub);
colnormidx = find(colnorm == 0);
if ~isempty(colnormidx)
for j = 1:length(colnormidx)
rand('state',j);
jcol = colnormidx(j);
Mcol = M(:,jcol);
truecol = find( abs(Mcol) > 1e-13 );
len = length(truecol);
rp = randperm(len);
chcol = truecol(rp(1:min(NumPerRow,len)));
Msub(chcol,jcol) = Mcol(chcol);
end
end
else
%%
%% MovieLens data set
%%
normM = sum(M.*M);
idx = find(normM == 0);
M = M(:,setdiff([1:size(M,2)],idx)); %% removed zero columns.
fprintf('\n***** removed %2.1d zero columns in M',length(idx));
Mt = M';
[nr,nc] = size(M);
nnzM = nnz(M);
NumElement = 10;
if (NumElement > 0)
rr = zeros(nnzM,1);
cc = zeros(nnzM,1);
vv = zeros(nnzM,1);
count = 0;
for i=1:nr
rand('state',i);
Mrow = full(Mt(:,i))';
truerow = find( abs(Mrow) > 1e-13);
len = length(truerow);
rp = randperm(len);
NumPerRow = min(max(NumElement,floor(len*0.5)),len);
%% NumPerRow = min(NumElement,len);
chrow = truerow(rp(1:NumPerRow));
idx = [1:NumPerRow];
rr(count+idx) = i*ones(NumPerRow,1);
cc(count+idx) = chrow;
vv(count+idx) = Mrow(chrow);
count = count + NumPerRow;
if (rem(i,1000)==0); fprintf('\n i = %2.1d',i); end
end
rr = rr(1:count); cc = cc(1:count); vv = vv(1:count);
Msub = spconvert([rr,cc,vv; nr,nc,0]);
colnorm = sum(Msub.*Msub);
colnormidx = find(colnorm == 0);
if ~isempty(colnormidx)
rr = zeros(nnzM,1);
cc = zeros(nnzM,1);
vv = zeros(nnzM,1);
count = 0;
for j = 1:length(colnormidx)
rand('state',j);
jcol = colnormidx(j);
Mcol = full(M(:,jcol));
truecol = find( abs(Mcol) > 1e-13 );
len = length(truecol);
rp = randperm(len);
NumPerCol = min(max(NumElement,floor(len*0.5)),len);
%% NumPerCol = min(NumElement,len);
chcol = truecol(rp(1:NumPerCol));
idx = [1:NumPerCol];
rr(count+idx) = chcol;
cc(count+idx) = jcol*ones(NumPerCol,1);
vv(count+idx) = Mcol(chcol);
count = count + NumPerCol;
end
rr = rr(1:count); cc = cc(1:count); vv = vv(1:count);
Msub = Msub + spconvert([rr,cc,vv; nr,nc,0]);
end
else
Msub = M;
end
end
B = sparse(Msub);
normB = sqrt(sum(B.*B));
zerocolidx = find(normB==0);
if ~isempty(zerocolidx)
error('***** B has zero columns');
end
nnzB = nnz(B);
%%
%% evaluate the regularization parameter mu
%%
options = [];
[Umax,Smax,Vmax] = lansvd(sparse(B),1,'L',options);
mumax = max(diag(Smax));
mu_scaling = 1e-3;
mutarget = mu_scaling*mumax;
%%
[II,JJ,bb] = find(B);
Jcol = compJcol(JJ);
Amap = @(X) Amap_MatComp(X,II,Jcol);
if (exist('mexspconvert')==3)
ATmap = @(y) mexspconvert(nr,nc,y,II,Jcol);
else
ATmap = @(y) spconvert([II,JJ,y; nr,nc,0]);
end
par.tol = 1e-3;
par.maxiter = 100;
par.verbose = 1;
par.plotyes = 1;
par.maxrank = 100;
par.truncation = 1;
par.truncation_gap = 20;
par.continuation_scaling = mu_scaling;
tstart = clock;
problem_type = 'NNLS';
[X,iter,time,sd,hist] = ...
APGL(nr,nc,problem_type,Amap,ATmap,bb,mutarget,0,par);
runhist.nr = nr;
runhist.nc = nc;
runhist.nnzB = nnz(B);
runhist.nnzM = nnz(M);
runhist.time = etime(clock,tstart);
runhist.iter = iter;
runhist.obj = hist.obj(end);
runhist.mu = mutarget;
runhist.mumax = mumax;
runhist.svp = hist.svp(end);
runhist.maxsvp = max(hist.svp);
runhist.maxsig = max(sd);
runhist.minsig = min(sd(find(sd>0)));
[nr,nc] = size(M);
[II,JJ,Mvec] = find(M.*(spones(M)-spones(B)));
Jcol = compJcol(JJ);
Xvec = Amap_MatComp(X,II,Jcol);
Rvec = Mvec-Xvec;
runhist.pMAE = mean(abs(Rvec));
runhist.pRMSE = sqrt(mean(Rvec.*Rvec));
[II,JJ,Mvec] = find(M);
Jcol = compJcol(JJ);
Xvec = Amap_MatComp(X,II,Jcol);
Rvec = Mvec-Xvec;
range = max(Mvec)-min(Mvec);
runhist.MAE = mean(abs(Rvec));
runhist.RMSE = sqrt(mean(Rvec.*Rvec));
runhist.range = range;
runhist.pNMAE = runhist.pMAE/range;
runhist.pNRMSE = runhist.pRMSE/range;
runhist.NMAE = runhist.MAE/range;
runhist.NRMSE = runhist.RMSE/range;
%%
%% report results in a table
%%
fprintf('\nProblem: %s, nr = %d, nc = %d,',fname,nr,nc);
fprintf(' nnz(B) = %d, nnz(B)/nr*nc = %2.1f%%',nnzB,nnzB/(nr*nc)*100)
fprintf('\nParameters: mu = %g',mutarget)
fprintf('\n-----------------------------------------------');
fprintf('------------------------------')
fprintf('\n iterations : %5.0d',runhist.iter);
fprintf('\n # singular : %5.0d',runhist.svp);
fprintf('\n obj value : %5.3e',runhist.obj);
fprintf('\n cpu time : %5.2e',runhist.time);
fprintf('\n MAE, pMAE, NMAE, pNMAE : %5.3e, %5.3e, %5.3e, %5.3e',...
runhist.MAE,runhist.pMAE,runhist.NMAE,runhist.pNMAE);
fprintf('\n RMSE, pRMSE, NRMSE, pNRMSE : %5.3e, %5.3e, %5.3e, %5.3e',...
runhist.RMSE,runhist.pRMSE,runhist.NRMSE,runhist.pNRMSE);
fprintf('\n-----------------------------------------------');
fprintf('------------------------------\n')
end
%%*************************************************************************