Building models with SAS Enterprise Miner, SAS Factory Miner, SAS Visual Data Mining and Machine Learning or just with programming

Cannot process Sas Enterprise Miner Job!

Accepted Solution Solved
Reply
Contributor
Posts: 68
Accepted Solution

Cannot process Sas Enterprise Miner Job!

Hi!

Iwas using Sas Enterprise Miner and when I imported data to process it was OK, but i had some error in sas em client, I didn't know this error of logic or sas miner server. The error logs was as below:

Please help me to fix them if impossible!

 

*------------------------------------------------------------*
User: cfcpyn
Date: December 08, 2017
Time: 12:49:27
Site: 11000944
Platform: AIX
Maintenance Release: 9.04.01M2P072314
EM Version: 13.2
*
*------------------------------------------------------------*
* Training Log
Date: December 08, 2017
Time: 12:49:13
*------------------------------------------------------------*
10847 proc freq data=EMWS1.Clus_VariableSet noprint;
10848 table ROLE*LEVEL/out=WORK.ClusMETA;
10849 run;

NOTE: There were 37 observations read from the data set EMWS1.CLUS_VARIABLESET.
NOTE: The data set WORK.CLUSMETA has 2 observations and 4 variables.
NOTE: PROCEDURE FREQ used (Total process time):
real time 0.07 seconds
cpu time 0.01 seconds


10850 proc print data=WORK.ClusMETA label noobs;
10851 var ROLE LEVEL COUNT;
10852 label ROLE = "%sysfunc(sasmsg(sashelp.dmine, meta_role_vlabel, NOQUOTE))" LEVEL = "%sysfunc(sasmsg(sashelp.dmine, meta_level_vlabel, NOQUOTE))" COUNT = "%sysfunc(sasmsg(sashelp.dmine, rpt_count_vlabel, NOQUOTE))";
10853 title9 ' ';
10854 title10 "%sysfunc(sasmsg(sashelp.dmine, rpt_varSummary_title , NOQUOTE))";
10855 run;

NOTE: There were 2 observations read from the data set WORK.CLUSMETA.
NOTE: The PROCEDURE PRINT printed page 1.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds


10856 title10;

10857 data WORK.M3MIDY5J;
10858 set WORK.M3MIDY5J;
10859 if role eq 'REJECTED' then role = 'INPUT';
10860 run;

NOTE: There were 37 observations read from the data set WORK.M3MIDY5J.
NOTE: The data set WORK.M3MIDY5J has 37 observations and 21 variables.
NOTE: DATA statement used (Total process time):
real time 0.02 seconds
cpu time 0.00 seconds


10869 *------------------------------------------------------------*;
10870 * Clus: Preliminary Clustering;
10871 *------------------------------------------------------------*;
10872 *------------------------------------------------------------* ;
10873 * Clus: DMDBClass Macro ;
10874 *------------------------------------------------------------* ;
10875 %macro DMDBClass;
10876 Area(ASC) Category(ASC) CrdCampaign(ASC) HomeCityName(ASC) HomeCityName1(ASC)
10877 HomeDistrictName(ASC) HomePhoneType(ASC) HomeResidenceType(ASC) JobTitle(ASC)
10878 LocaCampaign1(ASC) MARITAL_STATUS(ASC) NoBankCampaign(ASC) OfficePhoneType(ASC)
10879 PhoneWaiver(ASC) Qualification(ASC) Rec_Group(ASC) SUBCATEGORY(ASC)
10880 WOMonth(ASC) agreementno(ASC) biztype(ASC) industrytype1(ASC) product(ASC)
10881 sex(ASC) source(ASC)
10882 %mend DMDBClass;
10883 *------------------------------------------------------------* ;
10884 * Clus: DMDBVar Macro ;
10885 *------------------------------------------------------------* ;
10886 %macro DMDBVar;
10887 AGE DBR DBR_PTI EFFRATE MONTHLY_INCOME RemainingPOS TAR TENURE TimeOnCurJob
10888 WorkExperience YearOnOperation capital woprin
10889 %mend DMDBVar;
10890 *------------------------------------------------------------*;
10891 * Clus: Create DMDB;
10892 *------------------------------------------------------------*;
10893 proc dmdb batch data=EMWS1.Ids_DATA
10894 dmdbcat=WORK.Clus_DMDB
10895 maxlevel = 100000
10896 out=WORK.Clus_DMDB
10897 ;
10898 class %DMDBClass;
10899 var %DMDBVar;
10900 run;

NOTE: Records processed = 10482 Memory used = 511K.
NOTE: View EMWS1.IDS_DATA.VIEW used (Total process time):
real time 0.38 seconds
cpu time 0.18 seconds

NOTE: There were 10482 observations read from the data set CFCPUB.RECOVERY_SEG.
NOTE: There were 10482 observations read from the data set EMWS1.IDS_DATA.
NOTE: The data set WORK.CLUS_DMDB has 10482 observations and 37 variables.
NOTE: PROCEDURE DMDB used (Total process time):
real time 0.40 seconds
cpu time 0.18 seconds


10901 quit;
10902 *--- end code ---*;

10903 *------------------------------------------------------------* ;
10904 * Clus: Interval Inputs Macro ;
10905 *------------------------------------------------------------* ;
10906 %macro DMVQINTERVAL;
10907 AGE DBR DBR_PTI EFFRATE MONTHLY_INCOME RemainingPOS TAR TENURE TimeOnCurJob
10908 WorkExperience YearOnOperation capital woprin
10909 %mend DMVQINTERVAL;
10910 *------------------------------------------------------------* ;
10911 * Clus: Nominal Inputs Macro ;
10912 *------------------------------------------------------------* ;
10913 %macro DMVQNOMINAL;
10914 Area Category CrdCampaign HomeCityName HomeCityName1 HomeDistrictName
10915 HomePhoneType HomeResidenceType JobTitle LocaCampaign1 MARITAL_STATUS
10916 NoBankCampaign OfficePhoneType PhoneWaiver Qualification Rec_Group SUBCATEGORY
10917 WOMonth agreementno biztype industrytype1 product sex source
10918 %mend DMVQNOMINAL;
10919 *------------------------------------------------------------*;
10920 * Clus: Run DMVQ procedure;
10921 *------------------------------------------------------------*;
10922 title;
10923 options nodate;
10924 proc dmvq data=WORK.Clus_DMDB dmdbcat=WORK.Clus_DMDB std=STD nominal=GLM ordinal=RANK
10925 ;
NOTE: The training set WORK.CLUS_DMDB.DATA has 37 variable(s).
NOTE: The DMVQ statement has finished with return code=0 and status=begin.
10926 input %DMVQINTERVAL / level=interval;
NOTE: 13 input variable(s) defined for ID=I1.
NOTE: The INPUT statement has finished with return code=0 and status=variables.
10927 input %DMVQNOMINAL / level=nominal;
NOTE: 24 input variable(s) defined for ID=I2.
NOTE: The INPUT statement has finished with return code=0 and status=variables.
10928 VQ maxc = 50 clusname=_SEGMENT_ CLUSLABEL="Segment Id" DISTLABEL="Distance";
NOTE: A maximum of 50 clusters have been requested.
NOTE: The VQ statement has finished with return code=0 and status=architecture.
10929 MAKE outvar=EMWS1.Clus_OUTVAR;
WARNING: Variable NoBankCampaign is omitted from the analysis because it has only one category.
WARNING: Variable PhoneWaiver is omitted from the analysis because it has no usable categories.
WARNING: Variable SUBCATEGORY is omitted from the analysis because it has only one category.
WARNING: Variable product is omitted from the analysis because it has only one category.

NOTE: 37 input variable(s).
NOTE: Number of cases=10482
NOTE: Sum of frequencies=10482
NOTE: Sum of weights=10482
NOTE: VARDEF=DF
NOTE: Maximum number of categories=10482
NOTE: The total number of variables is 37 with dimensionality 10750.
NOTE: 33 variables will be used for clustering.
NOTE: Open output data set EMWS1.CLUS_OUTVAR.DATA with 10755 variables.
NOTE: The data set EMWS1.CLUS_OUTVAR has 4 observations and 10755 variables.
NOTE: The MAKE statement has finished with return code=0 and status=made.
10930 INITIAL radius=0
10931 ;
ERROR: 0 seeds were selected from data set WORK.CLUS_DMDB.DATA using the SEPARATE algorithm.
ERROR: All observations have missing values, or nonpositive weights or frequencies. No cluster seeds can be selected.
NOTE: The INITIAL statement has finished with return code=108 and status=initialized.
10932 TRAIN tech=FORGY
10933 ;
WARNING: TRAIN statement ignored. Type RUN; to continue running the procedure or QUIT; to stop.
10934 SAVE outstat=WORK.Clus_OUTSTAT outmean=EMWS1.Clus_OUTMEAN;
WARNING: SAVE statement ignored. Type RUN; to continue running the procedure or QUIT; to stop.
10935 code file="/sas-library/FI/FI/Workspaces/EMWS1/Clus/DMVQSCORECODE.sas"
10936 group=Clus
10937 ;
WARNING: CODE statement ignored. Type RUN; to continue running the procedure or QUIT; to stop.
10938 run;

10939 quit;

NOTE: The SAS System stopped processing this step because of errors.
NOTE: There were 10482 observations read from the data set WORK.CLUS_DMDB.
WARNING: The data set WORK.CLUS_OUTSTAT may be incomplete. When this step was stopped there were 0 observations and 0 variables.
WARNING: The data set EMWS1.CLUS_OUTMEAN may be incomplete. When this step was stopped there were 0 observations and 0 variables.
WARNING: Data set EMWS1.CLUS_OUTMEAN was not replaced because this step was stopped.
NOTE: PROCEDURE DMVQ used (Total process time):
real time 12.54 seconds
cpu time 7.61 seconds


*------------------------------------------------------------*
*
* ERROR: Run time error was encountered. The system error returned was 1008.
* Please report unresolved problems to Technical Support.
*
*------------------------------------------------------------*

 

Thanks so much!


Accepted Solutions
Solution
‎12-15-2017 06:41 PM
Super User
Posts: 13,508

Re: Cannot process Sas Enterprise Miner Job!

[ Edited ]

I am not familiar with the specific proc but when I see something like this:

ERROR: All observations have missing values, or nonpositive weights or frequencies. No cluster seeds can be selected.

It usually means that every record in the data set is missing values for at least one model or required-to-be-present variable. The missing variable could be different on each of the observations. Or a variable used for weights is missing or nonpositive.

 

Which would make this likely to be an input data issue.

 

I would check the variables used for completeness. You don't say how you brought the data in but there is possible if an import task or proc import was used that a variable that should be character was treated as numeric if the first rows of data had only numeric looking values and later rows with character data we set to missing.

View solution in original post


All Replies
Solution
‎12-15-2017 06:41 PM
Super User
Posts: 13,508

Re: Cannot process Sas Enterprise Miner Job!

[ Edited ]

I am not familiar with the specific proc but when I see something like this:

ERROR: All observations have missing values, or nonpositive weights or frequencies. No cluster seeds can be selected.

It usually means that every record in the data set is missing values for at least one model or required-to-be-present variable. The missing variable could be different on each of the observations. Or a variable used for weights is missing or nonpositive.

 

Which would make this likely to be an input data issue.

 

I would check the variables used for completeness. You don't say how you brought the data in but there is possible if an import task or proc import was used that a variable that should be character was treated as numeric if the first rows of data had only numeric looking values and later rows with character data we set to missing.

☑ This topic is solved.

Need further help from the community? Please ask a new question.

Discussion stats
  • 1 reply
  • 337 views
  • 1 like
  • 2 in conversation