Date: Fri, 29 Sep 2000 08:43:23 -0400
Reply-To: Mark.K.Moran@CENSUS.GOV
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Mark.K.Moran@CENSUS.GOV
Subject: Regular SAS Code in Enterprise Miner 3.01
Content-type: text/plain; charset=us-ascii
I am running SAS 6.12, using Enterprise Miner. This is all with the regular
program editor though, not the GUI.
I don't get what's going on. Seems to be a syntax problem near the end. Log
shown below.
-Mark
NOTE: AUTOEXEC processing beginning; file is
C:\PROGRA~1\sas\Addon\dmine3\autoexec.sas.
NOTE: Libref SAMPSIO was successfully assigned as follows:
Engine: V612
Physical Name: C:\program files\sas\Addon\dmine3\sample
NOTE: SAS Enterprise Miner version 3.01
NOTE: AUTOEXEC processing completed.
99 Options pageno=1;
100
101 libname neurout 'C:\moran004';
NOTE: Libref NEUROUT was successfully assigned as follows:
Engine: V612
Physical Name: C:\moran004
102
103 Data VarStr (keep=cfn indcat strold strnew strmske strmsrpt didctact
strcents genlistr
cfnli)
104 VarEqu (keep=cfn indcat equold equnew equmske equmsrpt didctact
equcents genliequ
cfnli);
105 input CFN $10. INDCAT 12-14 STROLD 16-23 STRNEW 25-32 STRMSKE $
STRMSRPT $ DIDCTACT $
STRCENTS 42-46 GENLISTR 48 CFNLI 50;
106 output VarStr;
107 input CFN $10. INDCAT 12-14 EQUOLD 16-23 EQUNEW 25-32 EQUMSKE $
EQUMSRPT $ DIDCTACT $
EQUCENTS 42-46 GENLIEQU 48 CFNLI 50;
108 output VarEqu;
109 cards;
NOTE: The data set WORK.VARSTR has 456 observations and 10 variables.
NOTE: The data set WORK.VAREQU has 456 observations and 10 variables.
NOTE: The DATA statement used 0.62 seconds.
1022 ;
1023 run;
1024
1025 Data Neurout.VarStr2;
1026 length CFNDUS13 $ 13;
1027 set VarStr;
1028 CFNDUS13=CFN||left(indcat);
1029 if CFNLI=1 THEN TARG3="WTCHG";
1030 else if CFNLI=0 AND GENLISTR=0 THEN TARG3="NOCHG";
1031 ELSE TARG3="UNK";
1032 if substr(left(Strold),1,1) in ('1','2') then Benfdstr='Y';
1033 else Benfdstr='N';
1034 stir=ranuni(144);
1035 run;
NOTE: Numeric values have been converted to character values at the places given
by:
(Line):(Column).
1028:20 1032:16
NOTE: The data set NEUROUT.VARSTR2 has 456 observations and 14 variables.
NOTE: The DATA statement used 0.42 seconds.
1036
1037 Data Neurout.VarEqu2;
1038 length CFNDUS13 $ 13;
1039 set VarEqu;
1040 CFNDUS13=CFN||left(indcat);
1041 if CFNLI=1 THEN TARG3="WTCHG";
1042 else if CFNLI=0 AND GENLIEQU=0 THEN TARG3="NOCHG";
1043 ELSE TARG3="UNK";
1044 if substr(left(Equold),1,1) in ('1','2') then Benfdequ='Y';
1045 else Benfdequ='N';
1046 stir=ranuni(312);
1047 run;
NOTE: Numeric values have been converted to character values at the places given
by:
(Line):(Column).
1040:20 1044:16
NOTE: The data set NEUROUT.VAREQU2 has 456 observations and 14 variables.
NOTE: The DATA statement used 0.23 seconds.
1048
1049
1050
1051 proc sort data=neurout.VarStr2 out=neurout.VarStr2 (drop= stir);
1052 by stir;
1053 run;
NOTE: The data set NEUROUT.VARSTR2 has 456 observations and 13 variables.
NOTE: The PROCEDURE SORT used 0.14 seconds.
1054
1055
1056
1057 proc sort data=neurout.VarEqu2 out=neurout.VarEqu2 (drop= stir);
1058 by stir;
1059 run;
NOTE: The data set NEUROUT.VAREQU2 has 456 observations and 13 variables.
NOTE: The PROCEDURE SORT used 0.13 seconds.
1060
1061 /* This is for the STRUCTURES dataset: */
1062
1063 data swtchgrs sothers;
1064 set neurout.varstr2;
1065 if targ3 = 'WTCHG' then output swtchgrs;
1066 else output sothers;
1067 run;
NOTE: The data set WORK.SWTCHGRS has 40 observations and 13 variables.
NOTE: The data set WORK.SOTHERS has 416 observations and 13 variables.
NOTE: The DATA statement used 0.19 seconds.
1068
1069 data spar_wtr spar_wva spar_wte;
1070 set swtchgrs;
1071 udrn = ranuni(153);
1072 if udrn > 0.4 then output spar_wtr;
1073 else if ((udrn > 0.3) and (udrn LE 0.4)) then output spar_wva;
1074 else if (udrn LE 0.3) then output spar_wte;
1075 run;
NOTE: The data set WORK.SPAR_WTR has 21 observations and 14 variables.
NOTE: The data set WORK.SPAR_WVA has 4 observations and 14 variables.
NOTE: The data set WORK.SPAR_WTE has 15 observations and 14 variables.
NOTE: The DATA statement used 0.16 seconds.
1076
1077 data spar_otr spar_ova spar_ote;
1078 set sothers;
1079 udrn = ranuni(163);
1080 if udrn > 0.4 then output spar_otr;
1081 else if ((udrn>0.3) and (udrn LE 0.4)) then output spar_ova;
1082 else if (udrn LE 0.3) then output spar_ote;
1083 run;
NOTE: The data set WORK.SPAR_OTR has 237 observations and 14 variables.
NOTE: The data set WORK.SPAR_OVA has 40 observations and 14 variables.
NOTE: The data set WORK.SPAR_OTE has 139 observations and 14 variables.
NOTE: The DATA statement used 0.25 seconds.
1084
1085
1086
1087 data ewtchgrs eothers;
1088 set neurout.varequ2;
1089 if targ3 = 'WTCHG' then output ewtchgrs;
1090 else output eothers;
1091 run;
NOTE: The data set WORK.EWTCHGRS has 39 observations and 13 variables.
NOTE: The data set WORK.EOTHERS has 417 observations and 13 variables.
NOTE: The DATA statement used 0.16 seconds.
1092
1093 data epar_wtr epar_wva epar_wte;
1094 set ewtchgrs;
1095 udrn = ranuni(153);
1096 if udrn > 0.4 then output epar_wtr;
1097 else if ((udrn > 0.3) and (udrn LE 0.4)) then output epar_wva;
1098 else if (udrn LE 0.3) then output epar_wte;
1099 run;
NOTE: The data set WORK.EPAR_WTR has 20 observations and 14 variables.
NOTE: The data set WORK.EPAR_WVA has 4 observations and 14 variables.
NOTE: The data set WORK.EPAR_WTE has 15 observations and 14 variables.
NOTE: The DATA statement used 0.11 seconds.
1100
1101 data epar_otr epar_ova epar_ote;
1102 set eothers;
1103 udrn = ranuni(163);
1104 if udrn > 0.4 then output epar_otr;
1105 else if ((udrn>0.3) and (udrn LE 0.4)) then output epar_ova;
1106 else if (udrn LE 0.3) then output epar_ote;
1107 run;
NOTE: The data set WORK.EPAR_OTR has 238 observations and 14 variables.
NOTE: The data set WORK.EPAR_OVA has 40 observations and 14 variables.
NOTE: The data set WORK.EPAR_OTE has 139 observations and 14 variables.
NOTE: The DATA statement used 0.22 seconds.
1108
1109
1110
1111 data neurout.sbetrain;
1112 set spar_wtr
1113 spar_otr;
1114 run;
NOTE: The data set NEUROUT.SBETRAIN has 258 observations and 14 variables.
NOTE: The DATA statement used 0.23 seconds.
1115
1116 data neurout.sbevalid;
1117 set spar_wva
1118 spar_ova;
1119 run;
NOTE: The data set NEUROUT.SBEVALID has 44 observations and 14 variables.
NOTE: The DATA statement used 0.28 seconds.
1120
1121 data neurout.sbetestd;
1122 set spar_wte
1123 spar_ote;
1124 run;
NOTE: The data set NEUROUT.SBETESTD has 154 observations and 14 variables.
NOTE: The DATA statement used 0.14 seconds.
1125
1126
1127
1128 data neurout.ebetrain;
1129 set epar_wtr
1130 epar_otr;
1131 run;
NOTE: The data set NEUROUT.EBETRAIN has 258 observations and 14 variables.
NOTE: The DATA statement used 0.23 seconds.
1132
1133 data neurout.ebevalid;
1134 set epar_wva
1135 epar_ova;
1136 run;
NOTE: The data set NEUROUT.EBEVALID has 44 observations and 14 variables.
NOTE: The DATA statement used 0.12 seconds.
1137
1138 data neurout.ebetestd;
1139 set epar_wte
1140 epar_ote;
1141 run;
NOTE: The data set NEUROUT.EBETESTD has 154 observations and 14 variables.
NOTE: The DATA statement used 0.13 seconds.
1142
1143 proc dmdb batch data=neurout.sbetrain out=sdmtrain dmdbcat=scadmtra;
1144 var strold strnew strcents;
1145 class strmske(ascending) strmsrpt(ascending) didctact(ascending) targ3;
1146 target targ3;
1147 run;
Records processed= 258 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.28 seconds.
1148
1149 proc dmdb batch data=neurout.sbevalid out=sdmvalid dmdbcat=scadmval;
1150 var strold strnew strcents;
1151 class strmske(ascending) strmsrpt(ascending) didctact(ascending) targ3;
1152 target targ3;
1153 run;
Records processed= 44 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.05 seconds.
1154
1155 proc dmdb batch data=neurout.sbetestd out=sdmtestd dmdbcat=scatestd;
1156 var strold strnew strcents;
1157 class strmske(ascending) strmsrpt(ascending) didctact(ascending) targ3;
1158 target targ3;
1159 run;
Records processed= 154 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.11 seconds.
1160
1161 proc dmdb batch data=neurout.ebetrain out=edmtrain dmdbcat=ecadmtra;
1162 var equold equnew equcents;
1163 class equmske(ascending) equmsrpt(ascending) didctact(ascending) targ3;
1164 target targ3;
1165 run;
Records processed= 258 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.07 seconds.
1166
1167 proc dmdb batch data=neurout.ebevalid out=edmvalid dmdbcat=ecadmval;
1168 var equold equnew equcents;
1169 class equmske(ascending) equmsrpt(ascending) didctact(ascending) targ3;
1170 target targ3;
1171 run;
Records processed= 44 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.16 seconds.
1172
1173 proc dmdb batch data=neurout.ebetestd out=edmtestd dmdbcat=ecatestd;
1174 var equold equnew equcents;
1175 class equmske(ascending) equmsrpt(ascending) didctact(ascending) targ3;
1176 target targ3;
1177 run;
Records processed= 154 Mem used = 511K.
NOTE: The PROCEDURE DMDB used 0.08 seconds.
1178
ERROR: File WORK.DMTRAIN.DATA does not exist.
NOTE: Closing the Neural Application.
NOTE: The SAS System stopped processing this step because of errors.
NOTE: The PROCEDURE NEURAL used 0.71 seconds.
1179 proc neural data=dmtrain;
1180 input strold strnew strcents / level=int;
1181 input strmske strmsrpt didctact / level=nom;
1182 target targ3 / level=nom id=cfndus13;
1183 archi glim;
1184 score data=betrain nodmdb out=betrain2;
1185 run;
1186
1187 proc tabulate data=betrain2 format=5.0;
ERROR: File WORK.BETRAIN2.DATA does not exist.
1188 class targ3 i_targ3;
1189 table targ3 all, i_targ3 all / misstext='0' rts=8;
1190 run;
NOTE: The SAS System stopped processing this step because of errors.
NOTE: The PROCEDURE TABULATE used 0.1 seconds.
