search for: train1

...code produced result only for 8 iterations and for 9th iteration it reaches to an error that ?subscript out of bonds? error. I don?t understand why Any help would be great thanks ####### for (i in 1:10) { fit1<-NULL; x<-NULL; x<-which(number==i) trainset<-d[-x,] testset<-d[x,] train1<-trainset[,-ncol(trainset)] train1<-train1[,-(1)] test_t<-testset[,-ncol(testset)] species_test<-as.factor(testset[,ncol(testset)]) test_t<-test_t[,-(1)] #### #CARET::TRAIN #### fit1<-train(train1,as.factor(trainset[,ncol(trainset)]),"svmpoly",trControl = train...

...########################################## Code ######################################### x<-NULL index<-cvsegments(nrow(data),10) for(i in 1:length(index)) { x<-matrix(index[i]) testset<-data[x[[1]],] trainset<-data[-x[[1]],] species<-as.factor(trainset[,ncol(trainset)]) train1<-trainset[,-ncol(trainset)] train1<-train1[,-(1)] test_t<-testset[,-ncol(testset)] species_test<-as.factor(testset[,ncol(testset)]) test_t<-test_t[,-(1)] model_true1 <- svm(train1,species) pred_true1<-predict(model_true1,test_t) stat_result<- confusionMatrix(pred_tru...

...iceSample <- sample(combined[,-c(1,2)],nvars, replace=FALSE) miceSample$pID50 <- combined$pID50 miceTestSample <- miceSample[47:55,] miceTrainSample <- miceSample[1:46,] fit.kknn <- kknn(pID50~., miceTrainSample, miceTestSample) table(miceTestSample$pID50, fit.kknn$fit) (fit.train1 <- train.kknn(pID50~., miceTrainSample, kmax=15, kernel=c("rectangular"), distance=1)) predictedTrain <- predict(fit.train1, miceTrainSample, miceTrainSample$pID50) pID50Train <- miceTrainSample$pID50 lmTrain <- lm(predictedTrain~pID50Train) slm <- summary(lmTrain) st...

...j, 0x00000100 | - train->type09.data[i] << 4 | - train->type07.data[i]); - nvkm_wr32(device, 0x10f918 + j, train->type01.data[i]); + static const u8 train0[] = { + 0x00, 0xff, 0x55, 0xaa, 0x33, 0xcc, + 0x00, 0xff, 0xff, 0x00, 0xff, 0x00, + }; + + static const u32 train1[] = { + 0x00000000, 0xffffffff, + 0x55555555, 0xaaaaaaaa, + 0x33333333, 0xcccccccc, + 0xf0f0f0f0, 0x0f0f0f0f, + 0x00ff00ff, 0xff00ff00, + 0x0000ffff, 0xffff0000, + }; + + if ((train->mask & 0x03c3) == 0x03c3) { + for (i = 0; i < 0x30; i++) { + for (j = 0; j < 8; j += 4) { +...

Hi, I have a question on read.table. I have a dataset with 273,000 lines and 195 columns. I used the read.table to load the data into R: trn<-read.table('train1.dat', header=F, sep='|', na.strings='.') I found it takes forever. then I run 1/10 of the data (test) using read.table again. And this time it finished quickly. So, there might be something wrong in my data format causing that problem. then, my question is, is there a way in R...

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...4 size, u32 align, u32 ncmin, } static int -gf100_ram_init(struct nvkm_ram *base) +gf100_ram_train_init_0(struct nvkm_ram *ram, struct gt215_ram_train *train) { - static const u8 train0[] = { - 0x00, 0xff, 0x55, 0xaa, 0x33, 0xcc, - 0x00, 0xff, 0xff, 0x00, 0xff, 0x00, - }; - static const u32 train1[] = { - 0x00000000, 0xffffffff, - 0x55555555, 0xaaaaaaaa, - 0x33333333, 0xcccccccc, - 0xf0f0f0f0, 0x0f0f0f0f, - 0x00ff00ff, 0xff00ff00, - 0x0000ffff, 0xffff0000, - }; - struct gf100_ram *ram = gf100_ram(base); - struct nvkm_device *device = ram->base.fb->subdev.device; - int i; + struct...

No, no, these will not implement Fermi reclocking. This set of patches contains some of the preparatory work that I deem stable enough to move upstream. Notable changes - Training pattern upload routines from GK104+ now shared with GT215+ - Timing calculation for Fermi - GDDR5 MR calculation from VBIOS timing table v1.0. Also useful for that pesky GT 240. - A routine to translate a VBIOS init

Two patches went missing as a result of PEBCAK. No v2 marks as nothing changed really. Just resending for easier enforcement of patch order in other people's trees. Sorry for the noise. Original message: No, no, these will not implement Fermi reclocking. This set of patches contains some of the preparatory work that I deem stable enough to move upstream. Notable changes - Training pattern

...gt;>> >>>>>#> log.reg >>>>> >>>>>#Call: glm(formula = train.class.var ~ predictors.train, family = >>>>>#binomial(link = "logit")) # >>>>>#Coefficients: >>>>># (Intercept) predictors.train1 predictors.train2 >>>>># 0.5105 -0.2945 -1.0811 >>>>># >>>>>#Degrees of Freedom: 39 Total (i.e. Null); 37 Residual >>>>>#Null Deviance: 55.45 >>>>>#Residual Deviance: 41.67...

...sk = 0777 valid users = +libsys +libmgmt +libacq +libtech +libarc +libcat +libcirc +librs +librss +libmdgc +libgift +libcoll +libtrain +libill +libgis +libarch +libstack +libaxs +libssc +studemp +studempl +eserials +pserials +syshead +ebooks mmcclint refstud catstud invalid users = +circdesk train1 train2 train3 train4 train5 train6 train7 train8 train9 train10 train11 train12 train13 train14 train15 train16 train17 train18 circstud madstud ssdata1 edox1 circdesk mlspine +librsch ~~~~~~~~~~~~~~~~~~~~~~~~ Daulton Theodore Carleton University Library, Systems Department Vmail: (613) 520-2600,...

...files1/user/common browseable = yes writeable = yes create mask = 0777 force create mode = 0777 directory mask = 0777 valid users = +libsys +libmgmt +libacq +libarc +libcat +libcirc +librs +libmdgc +libgift +libcoll +libtrain +libill +libcof +libgis invalid users = +circdesk train1 train2 train3 train4 train5 train6 train7 train8 train8 train10 train11 train12 train13 train14 train15 train16 train17 train18 # --------------------------------------- # Training Room # --------------------------------------- [training] comment = Training Shared Directory path...

...files1/user/common browseable = yes writeable = yes create mask = 0777 force create mode = 0777 directory mask = 0777 valid users = +libsys +libmgmt +libacq +libarc +libcat +libcirc +librs +libmdgc +libgift +libcoll +libtrain +libill +libcof +libgis invalid users = +circdesk train1 train2 train3 train4 train5 train6 train7 train8 train8 train10 train11 train12 train13 train14 train15 train16 train17 train18 # ------------------------------------ # Circulation Shared directory - 20051123 for dgavin # ------------------------------------ [circshr] comment = Circ Shared...