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run time error

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run time error

Run time error was encountered.  Please see the log for more details.
Hi ,
I am a new user of sas enterprize miner.
my question is about above window with run time error.
I used a data set / newral network/ score/ sas code
when I run this, in sas code i will get this error.
I confused with MARCO part in this diagram.
Would you please help me.

 


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‎11-24-2015 08:25 AM
Super Contributor
Posts: 337

Re: run time error

Your code seems OK, but for some reason EM thinks that you have not run your neural network yet:

 

8749 proc freq data=&EM_IMPORT_DATA;
ERROR: File EMWS3.NEURAL_TRAIN.DATA does not exist.

 

If you have this flow:

Data(node)-->Neural network(node)--> sas code(node)

 

click on your SAS Code node, go to Imported Data and browse or explore the training data. Confirm that data set exist, and your code should run.

 

good luck!

-M

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Regular Contributor
Posts: 161

Re: run time error

Did you have any attachments showing the error? Can you attach the log? 

Kannan Deivasigamani
New Contributor
Posts: 4

Re: run time error

This is one part of my LOG that have error:

 

8746 /* Neural Network fitting with 35 neurons and 50 iterations */
8747 title1 h=5 j=c f=swissb 'Table 1 Two Spirals Problem';
8748 title2 h=4 j=c '(Classification Matrix - Low Iteration)';


8749 proc freq data=&EM_IMPORT_DATA;
ERROR: File EMWS3.NEURAL_TRAIN.DATA does not exist.
8750 tables F_c*I_c / norow nocol nopercent missing;
ERROR: No data set open to look up variables.
ERROR: No data set open to look up variables.
8751 run;

NOTE: The SAS System stopped processing this step because of errors.
NOTE: PROCEDURE FREQ used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds

8752 title1 h=5 f=swissb 'Figure 2 Two Spirals Problem';
8753 title2 h=4 '(Predicted Membership - Low Iteration)';


8754 proc gplot data=&EM_IMPORT_DATA;
ERROR: File EMWS3.NEURAL_TRAIN.DATA does not exist.
8755 plot y*x=I_c / vaxis=axis1 haxis=axis2 legend=legend1 description="plot 2";
ERROR: No data set open to look up variables.
ERROR: No data set open to look up variables.
ERROR: No data set open to look up variables.
NOTE: The previous statement has been deleted.
8756 run;

New Contributor
Posts: 4

Re: run time error


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Solution
‎11-24-2015 08:25 AM
Super Contributor
Posts: 337

Re: run time error

Your code seems OK, but for some reason EM thinks that you have not run your neural network yet:

 

8749 proc freq data=&EM_IMPORT_DATA;
ERROR: File EMWS3.NEURAL_TRAIN.DATA does not exist.

 

If you have this flow:

Data(node)-->Neural network(node)--> sas code(node)

 

click on your SAS Code node, go to Imported Data and browse or explore the training data. Confirm that data set exist, and your code should run.

 

good luck!

-M

Super Contributor
Posts: 337

Re: run time error

Hi Matin,

So what exactly are you trying to do?

You mentioned that you have a SAS code node at the end of your flow. What are you trying to do with that SAS code? Hopefully there is a node to do what you are trying to do (this is the case 95% of the time).

Walk us through what you are trying to achieve and we'll help you debug the code you wrote on the SAS code node.

 

Thanks,

Miguel

New Contributor
Posts: 4

Re: run time error

[ Edited ]
Posted in reply to M_Maldonado

Thanks a lot for your reply.

Actually I am working on a homework for "data mining" class and It looks easy, however I stuck !

 

I just want to use Data(node)-->Neural network(node)--> sas code(node)

 

I attached what I have. I know it is not practical to ask question this way, but I really appreciate any help you can provide.

 

(How can I send sas data? in attachment?) 

 

options nodate nonumber;
goptions reset=all gunit=pct;

/* Define Graphics Symbols */
symbol1 c=b v=dot h=2 i=none; /* actual model */
symbol2 c=magenta v=circle h=2 i=none; /* observations */
symbol3 c=r v=none i=join; /* predicted model */

AXIS1 OFFSET=(2) length=65 LABEL=(F=Swissb H=3.5 A=90 R=270 "Y") minor=none
VALUE=(f=swissb H=3) ORDER = (-6 to 6 by 1) WIDTH=2;
AXIS2 OFFSET=(2) LENGTH=85 LABEL=(f=SWISSB H=3.5 "X") minor=none
VALUE=(f=swissb H=3) ORDER = (-8 to 8 by 1) WIDTH=2;

legend1 across=2 position=(top inside right)
value=(f=swissb h=2.5 "#1" "#2")
label=none mode=share frame;
legend2 across=3 position=(top inside right)
value=(f=swissb h=2.5 "True Curve" "Data" "Estimate")
label=none mode=share frame;

/* True Membership */
title1 h=5 f=swissb 'Figure 1 Two Spirals Problem';
title2 h=4 '(True Membership)';
proc gplot data=&EM_IMPORT_DATA;
plot y*x=c / vaxis=axis1 haxis=axis2 legend=legend1 description="plot 1";
run;
quit;

/* Neural Network fitting with 35 neurons and 50 iterations */
title1 h=5 j=c f=swissb 'Table 1 Two Spirals Problem';
title2 h=4 j=c '(Classification Matrix - Low Iteration)';
proc freq data=&EM_IMPORT_DATA;
tables F_c*I_c / norow nocol nopercent missing;
run;
title1 h=5 f=swissb 'Figure 2 Two Spirals Problem';
title2 h=4 '(Predicted Membership - Low Iteration)';
proc gplot data=&EM_IMPORT_DATA;
plot y*x=I_c / vaxis=axis1 haxis=axis2 legend=legend1 description="plot 2";
run;
quit;

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