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Data defines the model by dint of genetic programming, producing the best decile table.
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SAS Code for Ranking Predictors
Bruce Ratner, PhD |
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data IN;
input x1-x5 3.1;
cards;
0.1 0.7 9.1 0.3 0.2
0.0 0.1 2.2 0.7 0.8
0.1 0.2 1.7 0.4 0.5
0.1 0.4 1.8 0.2 0.2
0.1 0.6 4.6 0.8 0.6
0.0 0.2 0.2 1.0 0.2
0.2 0.0 1.0 1.0 0.4
0.1 0.4 1.9 0.7 0.1
0.0 0.8 0.0 0.2 0.3
0.0 0.6 3.3 0.2 0.9
;
run;
proc corr data=IN rank outp=out noprint;
with x5;
var x1-x4;
run;
data out1;
set out;
if _TYPE_='MEAN' then delete;
if _TYPE_='STD' then delete;
drop _NAME_;
run;
proc transpose data=out1
out=out2 (rename=( _1=n _2=CORR_X5 ) ) prefix=_;
run;
data out2;
set out2;
abs_corr=abs(corr_X5);
PREDICTOR=_NAME_;
run;
data out3;
set out2;
if n ge 0 and abs_corr ge .0;
run;
proc sort data=out3;by descending abs_corr;
run;
data out3;
set out3;
rank=_n_;
run;
proc print data=out3 noobs;
var rank PREDICTOR CORR_X5;
run;
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| For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at br@dmstat1.com. |
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br@dmstat1.com