It shows "The contents of the attachment doesn't match its file type."
It didn't work.
So, I post the code is as following,
%GLOBAL name rep1 rep2;
%LET name=GA;
%LET rep1=0;
%LET rep2=0;
/*GA for PLS*/
%MACRO Data;
%DO i=&rep1 %TO &rep2; /* i=1 to 1000*/
/*
******SECTION 1******
*/
/* GA algorithm */ /* This section is in PROC IML environment. */
PROC IML;
SUBMIT;
PROC IMPORT OUT= WORK.NIR140
DATAFILE= "D:\cal_data(&i).csv"
DBMS=CSV REPLACE;
GETNAMES=YES;
DATAROW=2;
PROC IMPORT OUT= WORK.NIR70
DATAFILE= "D:\val_data(&i).csv"
DBMS=CSV REPLACE;
GETNAMES=YES;
DATAROW=2;
RUN;
ENDSUBMIT;
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
/*start a "start finish module"*/
start uniform_cross(child1, child2, parent1, parent2);
child1 = parent1;
child2 = parent2;
do i = 1 to ncol(parent1);
r = uniform(1234);
if r<=0.5 then do;
child1[i] = parent2[i];
child2[i] = parent1[i];
end;
end;
finish;
/*end of start finish module*/
/*Start GA*/
start knapsack( x );
/*%SF*/
edit nir140 var _all_;
read all var _all_ into nir;
X_new=j (140, 351, 0); /*@@@140 40 : number of observations*/
do n=1 to 351;
if x[, n] =1
then do;
a=n+1;
X_new[,n]=nir[,a ];
end;
end;
data_new=nir[,1]||X_new;
create data_new from data_new;
append from data_new;
close data_new; /*PROC print data=data_new; proc print data=new_var; */
SUBMIT;
proc pls data=data_new method=pls cv=one NOCENTER NOSCALE ;
model COL1= COL2-COL352 / SOLUTION;
*ods output ParameterEstimates=coef;
ods output ResidualSummary=RS;
ods output CVResults=CVResults;
output out=score XSCORE=XSCORE;
RUN;
ENDSUBMIT;
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
EDIT RS var _all_;
READ all var _all_ into RS;
CLOSE RS;
EDIT CVResults var _all_;
read all var _all_ into CVResults;
CLOSE CVResults;
EDIT score var _all_;
READ all var _all_ into score;
CLOSE score;
/*calculating PRESS*/
RMPress=RS[, 2];
create RMPress from RMPress; /*P*/
append from RMPress;
close RMPress; /*P*/
/*factor numbers*/ /*x: extract only factor number from CVResults*/
f_no=CVResults[2,1];
create f_no from f_no; /*P*/
append from f_no;
close f_no; /*P*/
/*n*/
n=nrow(score);
/*RMSECV*/
/*factor numbers*/ /*x: extract only factor number from CVResults*/
minRMPress=RS[f_no+1, 2];
RMSECV=SQRT(((n-1)*(minRMPress##2))/n);
create RMSECV from RMSECV; /*P*/
append from RMSECV;
close RMSECV; /*P*/
/*end of %SF*/
return(RMSECV);
finish;
id = gasetup(2, 351, );
call gasetobj(id, 0, "knapsack" ); /* minimize objective module */
call gasetcro(id, 0.95, 0,"uniform_cross"); /* user crossover module */
call gasetmut(id,
0.01, /* mutation probabilty */
1);
call gasetsel(id, 2, /* carry 3 over to next generation */
0, /* dual tournament */
2 /* best-player-wins probabilty */
);
call gainit(id, 30, repeat({0,1},1, 351));
/*
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
*/
niter = 500; /*@@@@ now is 5, change niter to 1000*/
/*
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
*/
summary = j(niter,2);
mattrib summary [c = {"bestValue", "avgValue"}];
call gagetval(value, id);
summary[1,1] = value[1];
summary[1,2] = value[:];
do i = 1 to niter;
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
call garegen(id);
call gagetval(value, id);
summary[i,1] = value[1];
summary[i,2] = value[:];
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
end;
call gagetmem(mem, value, id, 1);
print "best member " mem[f = 1.0 l = ""],
"best value " value[l = ""];
iteration = t(1:niter);
print iteration summary;
call gaend(id);
create mem&i from mem;
append from mem;
close mem&i;
create value&i from value;
append from value;
close value&i;
create summary&i from summary;
append from summary;
close summary&i;
/* It is the end of GA algorithm. */
/*
DM LOG 'CLEAR';
DM OUTPUT 'CLEAR';
*/
%END;
%MEND;
%Data
QUIT;
