Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
1418 210907 396 81 3 79 30 869 120982 297 55 4 58 28 1530 176508 559 50 12 60 38 2172 179321 967 125 2 108 30 901 123185 270 40 1 49 22 463 52746 143 37 3 0 26 3201 385534 1562 63 0 121 25 371 33170 109 44 0 1 18 1192 101645 371 88 0 20 11 1583 149061 656 66 5 43 26 1439 165446 511 57 0 69 25 1764 237213 655 74 0 78 38 1495 173326 465 49 7 86 44 1373 133131 525 52 7 44 30 2187 258873 885 88 3 104 40 1491 180083 497 36 9 63 34 4041 324799 1436 108 0 158 47 1706 230964 612 43 4 102 30 2152 236785 865 75 3 77 31 1036 135473 385 32 0 82 23 1882 202925 567 44 7 115 36 1929 215147 639 85 0 101 36 2242 344297 963 86 1 80 30 1220 153935 398 56 5 50 25 1289 132943 410 50 7 83 39 2515 174724 966 135 0 123 34 2147 174415 801 63 0 73 31 2352 225548 892 81 5 81 31 1638 223632 513 52 0 105 33 1222 124817 469 44 0 47 25 1812 221698 683 113 0 105 33 1677 210767 643 39 3 94 35 1579 170266 535 73 4 44 42 1731 260561 625 48 1 114 43 807 84853 264 33 4 38 30 2452 294424 992 59 2 107 33 829 101011 238 41 0 30 13 1940 215641 818 69 0 71 32 2662 325107 937 64 0 84 36 186 7176 70 1 0 0 0 1499 167542 507 59 2 59 28 865 106408 260 32 1 33 14 1793 96560 503 129 0 42 17 2527 265769 927 37 2 96 32 2747 269651 1269 31 10 106 30 1324 149112 537 65 6 56 35 2702 175824 910 107 0 57 20 1383 152871 532 74 5 59 28 1179 111665 345 54 4 39 28 2099 116408 918 76 1 34 39 4308 362301 1635 715 2 76 34 918 78800 330 57 2 20 26 1831 183167 557 66 0 91 39 3373 277965 1178 106 8 115 39 1713 150629 740 54 3 85 33 1438 168809 452 32 0 76 28 496 24188 218 20 0 8 4 2253 329267 764 71 8 79 39 744 65029 255 21 5 21 18 1161 101097 454 70 3 30 14 2352 218946 866 112 1 76 29 2144 244052 574 66 5 101 44 4691 341570 1276 190 1 94 21 1112 103597 379 66 1 27 16 2694 233328 825 165 5 92 28 1973 256462 798 56 0 123 35 1769 206161 663 61 12 75 28 3148 311473 1069 53 8 128 38 2474 235800 921 127 8 105 23 2084 177939 858 63 8 55 36 1954 207176 711 38 8 56 32 1226 196553 503 50 2 41 29 1389 174184 382 52 0 72 25 1496 143246 464 42 5 67 27 2269 187559 717 76 8 75 36 1833 187681 690 67 2 114 28 1268 119016 462 50 5 118 23 1943 182192 657 53 12 77 40 893 73566 385 39 6 22 23 1762 194979 577 50 7 66 40 1403 167488 619 77 2 69 28 1425 143756 479 57 0 105 34 1857 275541 817 73 4 116 33 1840 243199 752 34 3 88 28 1502 182999 430 39 6 73 34 1441 135649 451 46 2 99 30 1420 152299 537 63 0 62 33 1416 120221 519 35 1 53 22 2970 346485 1000 106 0 118 38 1317 145790 637 43 5 30 26 1644 193339 465 47 2 100 35 870 80953 437 31 0 49 8 1654 122774 711 162 0 24 24 1054 130585 299 57 5 67 29 937 112611 248 36 0 46 20 3004 286468 1162 263 1 57 29 2008 241066 714 78 0 75 45 2547 148446 905 63 1 135 37 1885 204713 649 54 1 68 33 1626 182079 512 63 2 124 33 1468 140344 472 77 6 33 25 2445 220516 905 79 1 98 32 1964 243060 786 110 4 58 29 1381 162765 489 56 2 68 28 1369 182613 479 56 3 81 28 1659 232138 617 43 0 131 31 2888 265318 925 111 10 110 52 1290 85574 351 71 0 37 21 2845 310839 1144 62 9 130 24 1982 225060 669 56 7 93 41 1904 232317 707 74 0 118 33 1391 144966 458 60 0 39 32 602 43287 214 43 4 13 19 1743 155754 599 68 4 74 20 1559 164709 572 53 0 81 31 2014 201940 897 87 0 109 31 2143 235454 819 46 0 151 32 2146 220801 720 105 1 51 18 874 99466 273 32 0 28 23 1590 92661 508 133 1 40 17 1590 133328 506 79 0 56 20 1210 61361 451 51 0 27 12 2072 125930 699 207 4 37 17 1281 100750 407 67 0 83 30 1401 224549 465 47 4 54 31 834 82316 245 34 4 27 10 1105 102010 370 66 3 28 13 1272 101523 316 76 0 59 22 1944 243511 603 65 0 133 42 391 22938 154 9 0 12 1 761 41566 229 42 5 0 9 1605 152474 577 45 0 106 32 530 61857 192 25 4 23 11 1988 99923 617 115 0 44 25 1386 132487 411 97 0 71 36 2395 317394 975 53 1 116 31 387 21054 146 2 0 4 0 1742 209641 705 52 5 62 24 620 22648 184 44 0 12 13 449 31414 200 22 0 18 8 800 46698 274 35 0 14 13 1684 131698 502 74 0 60 19 1050 91735 382 103 0 7 18 2699 244749 964 144 2 98 33 1606 184510 537 60 7 64 40 1502 79863 438 134 1 29 22 1204 128423 369 89 8 32 38 1138 97839 417 42 2 25 24 568 38214 276 52 0 16 8 1459 151101 514 98 2 48 35 2158 272458 822 99 0 100 43 1111 172494 389 52 0 46 43 1421 108043 466 29 1 45 14 2833 328107 1255 125 3 129 41 1955 250579 694 106 0 130 38 2922 351067 1024 95 3 136 45 1002 158015 400 40 0 59 31 1060 98866 397 140 0 25 13 956 85439 350 43 0 32 28 2186 229242 719 128 4 63 31 3604 351619 1277 142 4 95 40 1035 84207 356 73 11 14 30 1417 120445 457 72 0 36 16 3261 324598 1402 128 0 113 37 1587 131069 600 61 4 47 30 1424 204271 480 73 0 92 35 1701 165543 595 148 1 70 32 1249 141722 436 64 0 19 27 946 116048 230 45 0 50 20 1926 250047 651 58 0 41 18 3352 299775 1367 97 9 91 31 1641 195838 564 50 1 111 31 2035 173260 716 37 3 41 21 2312 254488 747 50 10 120 39 1369 104389 467 105 5 135 41 1577 136084 671 69 0 27 13 2201 199476 861 46 2 87 32 961 92499 319 57 0 25 18 1900 224330 612 52 1 131 39 1254 135781 433 98 2 45 14 1335 74408 434 61 4 29 7 1597 81240 503 89 0 58 17 207 14688 85 0 0 4 0 1645 181633 564 48 2 47 30 2429 271856 824 91 1 109 37 151 7199 74 0 0 7 0 474 46660 259 7 0 12 5 141 17547 69 3 0 0 1 1639 133368 535 54 1 37 16 872 95227 239 70 0 37 32 1318 152601 438 36 2 46 24 1018 98146 459 37 0 15 17 1383 79619 426 123 3 42 11 1314 59194 288 247 6 7 24 1335 139942 498 46 0 54 22 1403 118612 454 72 2 54 12 910 72880 376 41 0 14 19 616 65475 225 24 2 16 13 1407 99643 555 45 1 33 17 771 71965 252 33 1 32 15 766 77272 208 27 2 21 16 473 49289 130 36 1 15 24 1376 135131 481 87 0 38 15 1232 108446 389 90 1 22 17 1521 89746 565 114 3 28 18 572 44296 173 31 0 10 20 1059 77648 278 45 0 31 16 1544 181528 609 69 0 32 16 1230 134019 422 51 0 32 18 1206 124064 445 34 1 43 22 1205 92630 387 60 4 27 8 1255 121848 339 45 0 37 17 613 52915 181 54 0 20 18 721 81872 245 25 0 32 16 1109 58981 384 38 7 0 23 740 53515 212 52 2 5 22 1126 60812 399 67 0 26 13 728 56375 229 74 7 10 13 689 65490 224 38 3 27 16 592 80949 203 30 0 11 16 995 76302 333 26 0 29 20 1613 104011 384 67 6 25 22 2048 98104 636 132 2 55 17 705 67989 185 42 0 23 18 301 30989 93 35 0 5 17 1803 135458 581 118 3 43 12 799 73504 248 68 0 23 7 861 63123 304 43 1 34 17 1186 61254 344 76 1 36 14 1451 74914 407 64 0 35 23 628 31774 170 48 1 0 17 1161 81437 312 64 0 37 14 1463 87186 507 56 0 28 15 742 50090 224 71 0 16 17 979 65745 340 75 0 26 21 675 56653 168 39 0 38 18 1241 158399 443 42 0 23 18 676 46455 204 39 0 22 17 1049 73624 367 93 0 30 17 620 38395 210 38 0 16 16 1081 91899 335 60 0 18 15 1688 139526 364 71 0 28 21 736 52164 178 52 0 32 16 617 51567 206 27 2 21 14 812 70551 279 59 0 23 15 1051 84856 387 40 1 29 17 1656 102538 490 79 1 50 15 705 86678 238 44 0 12 15 945 85709 343 65 0 21 10 554 34662 232 10 0 18 6 1597 150580 530 124 0 27 22 982 99611 291 81 0 41 21 222 19349 67 15 0 13 1 1212 99373 397 92 1 12 18 1143 86230 467 42 0 21 17 435 30837 178 10 0 8 4 532 31706 175 24 0 26 10 882 89806 299 64 0 27 16 608 62088 154 45 1 13 16 459 40151 106 22 0 16 9 578 27634 189 56 0 2 16 826 76990 194 94 0 42 17 509 37460 135 19 0 5 7 717 54157 201 35 0 37 15 637 49862 207 32 0 17 14 857 84337 280 35 0 38 14 830 64175 260 48 0 37 18 652 59382 227 49 0 29 12 707 119308 239 48 0 32 16 954 76702 333 62 0 35 21 1461 103425 428 96 1 17 19 672 70344 230 45 0 20 16 778 43410 292 63 0 7 1 1141 104838 350 71 1 46 16 680 62215 186 26 0 24 10 1090 69304 326 48 6 40 19 616 53117 155 29 3 3 12 285 19764 75 19 1 10 2 1145 86680 361 45 2 37 14 733 84105 261 45 0 17 17 888 77945 299 67 0 28 19 849 89113 300 30 0 19 14 1182 91005 450 36 3 29 11 528 40248 183 34 1 8 4 642 64187 238 36 0 10 16 947 50857 165 34 0 15 20 819 56613 234 37 1 15 12 757 62792 176 46 0 28 15 894 72535 329 44 0 17 16
Names of X columns:
pageviews time compinfo comppr sharedcomp bloggedcomp compreviewed
Endogenous Variable (Column Number)
Categorization
none
none
quantiles
hclust
equal
Number of categories (only if categorization<>none)
Cross-Validation? (only if categorization<>none)
no
no
yes
Chart options
R Code
library(party) library(Hmisc) par1 <- as.numeric(par1) par3 <- as.numeric(par3) x <- data.frame(t(y)) is.data.frame(x) x <- x[!is.na(x[,par1]),] k <- length(x[1,]) n <- length(x[,1]) colnames(x)[par1] x[,par1] if (par2 == 'kmeans') { cl <- kmeans(x[,par1], par3) print(cl) clm <- matrix(cbind(cl$centers,1:par3),ncol=2) clm <- clm[sort.list(clm[,1]),] for (i in 1:par3) { cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') } cl$cluster <- as.factor(cl$cluster) print(cl$cluster) x[,par1] <- cl$cluster } if (par2 == 'quantiles') { x[,par1] <- cut2(x[,par1],g=par3) } if (par2 == 'hclust') { hc <- hclust(dist(x[,par1])^2, 'cen') print(hc) memb <- cutree(hc, k = par3) dum <- c(mean(x[memb==1,par1])) for (i in 2:par3) { dum <- c(dum, mean(x[memb==i,par1])) } hcm <- matrix(cbind(dum,1:par3),ncol=2) hcm <- hcm[sort.list(hcm[,1]),] for (i in 1:par3) { memb[memb==hcm[i,2]] <- paste('C',i,sep='') } memb <- as.factor(memb) print(memb) x[,par1] <- memb } if (par2=='equal') { ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) x[,par1] <- as.factor(ed) } table(x[,par1]) colnames(x) colnames(x)[par1] x[,par1] if (par2 == 'none') { m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) } load(file='createtable') if (par2 != 'none') { m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) if (par4=='yes') { a<-table.start() a<-table.row.start(a) a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'',1,TRUE) a<-table.element(a,'Prediction (training)',par3+1,TRUE) a<-table.element(a,'Prediction (testing)',par3+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Actual',1,TRUE) for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) a<-table.element(a,'CV',1,TRUE) for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) a<-table.element(a,'CV',1,TRUE) a<-table.row.end(a) for (i in 1:10) { ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) if (i==1) { m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) m.ct.i.actu <- x[ind==1,par1] m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) m.ct.x.actu <- x[ind==2,par1] } else { m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) } } print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) numer <- 0 for (i in 1:par3) { print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) numer <- numer + m.ct.i.tab[i,i] } print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) numer <- 0 for (i in 1:par3) { print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) numer <- numer + m.ct.x.tab[i,i] } print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) for (i in 1:par3) { a<-table.row.start(a) a<-table.element(a,paste('C',i,sep=''),1,TRUE) for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,'Overall',1,TRUE) for (jjj in 1:par3) a<-table.element(a,'-') a<-table.element(a,round(m.ct.i.cp,4)) for (jjj in 1:par3) a<-table.element(a,'-') a<-table.element(a,round(m.ct.x.cp,4)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') } } m bitmap(file='test1.png') plot(m) dev.off() bitmap(file='test1a.png') plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') dev.off() if (par2 == 'none') { forec <- predict(m) result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) colnames(result) <- c('Actuals','Forecasts','Residuals') print(result) } if (par2 != 'none') { print(cbind(as.factor(x[,par1]),predict(m))) myt <- table(as.factor(x[,par1]),predict(m)) print(myt) } bitmap(file='test2.png') if(par2=='none') { op <- par(mfrow=c(2,2)) plot(density(result$Actuals),main='Kernel Density Plot of Actuals') plot(density(result$Residuals),main='Kernel Density Plot of Residuals') plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') par(op) } if(par2!='none') { plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') } dev.off() if (par2 == 'none') { detcoef <- cor(result$Forecasts,result$Actuals) a<-table.start() a<-table.row.start(a) a<-table.element(a,'Goodness of Fit',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Correlation',1,TRUE) a<-table.element(a,round(detcoef,4)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'R-squared',1,TRUE) a<-table.element(a,round(detcoef*detcoef,4)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'RMSE',1,TRUE) a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'#',header=TRUE) a<-table.element(a,'Actuals',header=TRUE) a<-table.element(a,'Forecasts',header=TRUE) a<-table.element(a,'Residuals',header=TRUE) a<-table.row.end(a) for (i in 1:length(result$Actuals)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,result$Actuals[i]) a<-table.element(a,result$Forecasts[i]) a<-table.element(a,result$Residuals[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') } if (par2 != 'none') { a<-table.start() a<-table.row.start(a) a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'',1,TRUE) for (i in 1:par3) { a<-table.element(a,paste('C',i,sep=''),1,TRUE) } a<-table.row.end(a) for (i in 1:par3) { a<-table.row.start(a) a<-table.element(a,paste('C',i,sep=''),1,TRUE) for (j in 1:par3) { a<-table.element(a,myt[i,j]) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') }
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation