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NKormanik
Barite | Level 11

As I'm understanding things, PLS regression comes up with a number of 'components.'  But how do these components tell us which of the original predictors is most important?

 

Thanks!

Nicholas Kormanik

 

1 ACCEPTED SOLUTION

Accepted Solutions
Ksharp
Super User
There is VIP plot you can refer to .

ods graphics on/width=1000px height=500px;
ods output VariableImportancePlot= VariableImportancePlot;
proc pls data=class missing=em nfac=2 plot=(ParmProfiles VIP) details; * cv=split cvtest(seed=12345);
class sex;
model age=weight height sex;
output out=x predicted=p;
run;
proc sort data=VariableImportancePlot;
by descending VIP;
run;

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7 REPLIES 7
Ksharp
Super User
There is VIP plot you can refer to .

ods graphics on/width=1000px height=500px;
ods output VariableImportancePlot= VariableImportancePlot;
proc pls data=class missing=em nfac=2 plot=(ParmProfiles VIP) details; * cv=split cvtest(seed=12345);
class sex;
model age=weight height sex;
output out=x predicted=p;
run;
proc sort data=VariableImportancePlot;
by descending VIP;
run;
PaigeMiller
Diamond | Level 26

The variables with high loadings (either positive or negative) are the important variables in that component. There's no real cutoff, the meaning of "high" is relative to the other loadings in that component.

 

The loadings are available via the DETAILS option of the PROC PLS statement. You can save the loadings to a SAS data set if you want via

 

ods output xloadings=xloadings;
--
Paige Miller
NKormanik
Barite | Level 11

@Ksharp @PaigeMiller   You guys rock.  Thanks so much!

 

 

 

NKormanik
Barite | Level 11
@Ksharp Noticed that your labels in the above graph are in Chinese.

How about that....
Ksharp
Super User
?? I am from China and running Chinese version SAS. If you are running English version SAS with same code , You would get English result . It is called Variables Important Plot . a.k.a VIP
NKormanik
Barite | Level 11

@Ksharp   Yes, I know.  Mainland, would be my guess.  SAS with everything in Chinese just seemed even more overwhelming than SAS in English.  Like, OMG!!

 

 

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