You may try PROC QUANTSELECT to perform Support Vector Machine (SVM) classification with LASSO penalty. An example is as follows:
/* Start: data simulation */
%let seed=111;
Data raw;
array x[10];
do i=1 to 1000;
x0=1; /* regressor for estimating bias parameter */
do j=1 to 10;
x
end;
y = 2*((3*x1+2*x2+x3+1+0.1*rannor(&seed))>0)-1; /*So the true model is proportional to (bias=1, x1=3, x2=2, x1=1).*/
output;
end;
run;
/* End: data simulation */
/* TransformSVM2QR macro pre-processes raw data for using QUANTSELECT.*/
%macro TransformSVM2QR(raw);
data transferred_&raw;
set &raw;
%do j=1 %to 10;
x&j = y*x&j;
%end;
bias=y;
y=1;
run;
%mend TransformSVM2QR;
%TransformSVM2QR(raw);
ods graphics on;
proc quantselect data=transferred_raw plot=all;
model y= bias x1-x10/quantile=1 noint selection=lasso(choose=validate include=1 sh=3);
partition fraction(validate=0.2);
run;
Available on demand!
Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.