When I use proc logistic with SCORE statement,
I wonder if there is a way of setting the cut-off value to help decision?
I also saw a PRIOREVENT statement in the proc logistic,
I wonder what doese this statement mean?
No. If you put validate table in score statement, you can generate Confuse Matrix. data train valid; set sashelp.class; if _n_ le 12 then output train; else output valid; run; proc logistic data=train; model sex=weight height age/ ctable; score data=valid out=score; run; proc tabulate data=score; class f_sex i_sex; table f_sex,i_sex; run;
proc logistic data=sashelp.class; model sex=weight height age/ ctable; run;
Thanks Ksharp,
As I have both training and validation set, I would be more interested in the confusion matrix for my validation data.
If you use proc logist data=taining; model y = x1 x2 x3 / CTABLE pprob=0.3; score data= validation; run;, then the confusion matrix from output would be probably for the training set instead of validation set. Am I right? So How can I create a confusion matrix for my validation data?
No. If you put validate table in score statement, you can generate Confuse Matrix. data train valid; set sashelp.class; if _n_ le 12 then output train; else output valid; run; proc logistic data=train; model sex=weight height age/ ctable; score data=valid out=score; run; proc tabulate data=score; class f_sex i_sex; table f_sex,i_sex; run;
Thanks KSharp,
When I modified my input like the following:
proc logistic data=train des;
model default=&selected PLOTS / CTABLE pprob=0.5;
score data=valid
out=scoval
outroc=roc;
run;
I will have the following warning message:
WARNING: Some plots have more than 5000 observations and are suppressed. Specify the
PLOTS(MAXPOINTS=NONE) option in the PROC LOGISTIC statement to display the plots.
However, this message will disappear if I remove the CTABLE STATMENT.
You can use the following to suppress these warning info. ods select none; proc logistic......... ods select all;
It looks like there is a complete explanation and example for multinomial response in the SAS note
Most of the syntax and ideas should translate to the case of a binary response, since binary is a special case of multinomial.
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