Dear Wendy  Sorry i did not make it clear on my objective and questions. Basically i want to use ROC curve to compare between classification models such as  picture below :     i got this infor from SAS youtube link  below:  https://www.youtube.com/watch?v=KMV5OtgTUUc   The understanding i have from SAS video above is, the instructor was running each classification model and score them. At the end of it, the instructor used Proc access to combined multiple model and compared them using the ROC chart above.      i have tried on HPSplit procedure and managed to score them successfully as below using sampsio.HMEQ sample  the output results containing  the probability value for train and validate dataset like below.        HPSplit scoring code used:    ods graphics on; proc hpsplit data=hmeq maxdepth=5; class Bad Delinq Derog Job nInq Reason; model Bad(event='1') = Delinq Derog Job nInq Reason CLAge CLNo DebtInc Loan MortDue Value YoJ; prune costcomplexity; partition fraction(validate=0.3 seed=1234567); code file="/ABC/hpsplexc.sas"; run;   data scored; set hmeq; %include '/lustre/home/1000151442/hpsplexc.sas'; run;   Now ,  I am  trying to simulate the same thing, same dataset using HPForest procedure.       proc hpsample data= sampsio.HMEQ out=hmeq sampobs=1788 seed=1234567 partition; Class Bad Delinq Derog Job nInq Reason ; run; proc hpforest data=work.hmeq maxtrees= 500 vars_to_try=4 seed=600 maxdepth=50 leafsize=6 alpha= 0.05; target Bad/ level=binary; input Delinq Derog Job nInq Reason / level=nominal; Partition roleVar=_partind_(train='0' validate='1') ; ods output fitstatistics = fit; save file = "/&outdir/abc.sas"; run; proc hp4score data=work.hmeq; id Bad; score file="/&outdir/abc.sas" out=Score123; run; proc print data=Score123; run;   Output results :   i couldn't get the probablity value for V_BAD0 & V_BAD1 from HPForest like HPSplit above.     Kindly guide me on this.    Many thanks!                       ... View more

Dear Wendy  Thank you for your great help. Yes! i am able to use the HPSample to split my data for the HPForest procedure as below:    proc hpsample data=&prepped_data. out=hpforest.split sampobs=640 seed=1234567 partition; Class &target. ; var &interval_inputs. ; run; Proc Freq data=hpforest.split; run; PROC HPFOREST DATA=&prepped_data1. MAXTREES= 200 VARS_TO_TRY=5 seed=600 trainfraction=0.6 maxdepth=50 leafsize=6 alpha= 0.1; TARGET &target. / LEVEL=Nominal; INPUT &interval_inputs. /LEVEL=INTERVAL; Partition roleVar=_partind_(train='1' validate='0'); ODS OUTPUT VARIABLEIMPORTANCE=LOSS_REDUCTION_IMPORTANCE; ODS OUTPUT FITSTATISTICS=FIR_STATISTICS; save file="&outdir/CTGF.sas"; RUN; /* COMMAND BELOW ENABLE YOU TO PRINT SPECIFIC OUTPUT RESULTS.*/; PROC PRINT DATA=WORK.FIR_STATISTICS; PROC PRINT DATA=WORK.LOSS_REDUCTION_IMPORTANCE; run; Allow me to ask further questions on HP Forest. Q1. How can i use the partition to split the LOSS_REDUCTION_IMPORTANCE into Train & Validate graphs ? Q2. How can i score the HPForest model? i could not find the right information for me to do so. Kindly guide me on this. Many Thanks! Jimmy     ... View more