Are you doing some analysis Like decision tree ? I pick up 0.2 as correlation coefficient benchmark . data x; array x{*} a1-a20; do j=1 to 100; do i=1 to dim(x); x{i}=ranuni(1234); end; output; end; drop i j; run; %let corr=0.2; proc sql noprint; select name into : list separated by ' '   from dictionary.columns    where libname='WORK' and memname='X'; quit; %macro decision; %let i=1; %do %while(1); proc corr data=x outp=person(where=(_TYPE_='CORR')) noprint; var &list ; run; data temp; set person; array x{*} a: ; length var $ 40; do i=1 to dim(x);   if x{i} eq 1 then leave;    else if abs(x{i}) ge &corr then do;                                   corr=x{i};                                   var=_name_; output;                                   var=vname(x{i}); output;                                  end; end; keep corr var; run; proc sql ; create table data_&i as select distinct var from temp; %if &sqlobs = 0 %then %do; create table data_&i as select _name_ as var from person; quit; %return; %end; select name into : list separated by ' '   from dictionary.columns    where libname='WORK' and memname='PERSON' and name not in (select distinct var from temp) and  name not in ('_NAME_' '_TYPE_'); quit; %let i=%eval(&i+1) ; %end; %mend decision; %decision Ksharp 消息编辑者为：xia keshan ... View more