search for: breastcancer

Dear All, I'm getting a error while trying to apply the BreastCancer dataset (package=mlbench) to kknn (package=kknn) that I don't understand as I'm new to R. The codes are as follow: rm = (list = ls()) library(mlbench) data(BreastCancer) library(kknn) BCancer = na.omit(BreastCancer) d = dim(BCancer)[1] i1 = seq(1, d, 2) i2 = seq(2, d, 2) t1 = BC...

....nuclei has 16 missing values and is used for the first split, but the missing values are not listed in either set of factors. (I have the same question for missing values among numeric [non-factor] values, but I assume the answer is similar.) > require(party) > require(mlbench) > data(BreastCancer) > BreastCancer$Id <- NULL > ct <- ctree(Class ~ . , data=BreastCancer, controls = ctree_control(maxdepth = 1)) > ct Conditional inference tree with 2 terminal nodes Response: Class Inputs: Cl.thickness, Cell.size, Cell.shape, Marg.adhesion, Epith.c.size, Bare.nuclei, B...

R-help, I am trying to perform a basic anlaysis of the BreastCancer data from "mlbench" using the svm() function in "e1071". I use the following code library("e1071") library("mlbench") data(BreastCancer) BC <- subset(BreastCancer, select=-Id) pairs(BC) model <- svm(Class ~ ., data=BC, cross=10) ## plot(model, BC, )...

...ive some comments? **************************** someguys use the following codes to plot, but I can not use the treeresponse commad in randomforest object directly. # create model using random forest and bagging ensemble using conditional inference trees 035 x.cf <- cforest(Class ~ ., data=BreastCancer[ind == 1,], control = cforest_unbiased(mtry = ncol(BreastCancer)-2)) 036 x.cf.pred <- predict(x.cf, newdata=BreastCancer[ind == 2,]) 037 x.cf.prob <- 1- unlist(treeresponse(x.cf, BreastCancer[ind == 2,]), use.names=F)[seq(1,nrow(BreastCancer[ind == 2,])*2,2)] 038 -- Sincerely...

...d it to a bad mail or if I am not very clear. So my problem is about the use of rfImpute from randomForest package. I am interested in imputations of missing values and I read that randomForest can make it. So i write the following code : set.seed(100); library(mlbench) library(randomForest) data(BreastCancer) summary(BreastCancer) data=BreastCancer[,-1] data=data[!is.na(data[,"Bare.nuclei"]),] summary(data) is.factor(data$Cl.thickness)# OK ##########selection of missing values###### x=1:nrow(data) sample1=sample(x,70) sample3=sample(x,70) sample5=sample(x,70) ##########replace by missin...

Hi Everybody, i again have the problem in using tune.knn(), its giving an error saying missing values are not allowed.... again here is the script for BreastCancer Data, library(e1071) library(mda) trdata<-data.frame(train,row.names=NULL) attach(trdata) xtr <- subset(trdata, select = -Class) ytr <- Class bestpara <-tune.knn(xtr,ytr, k = 1:25, tunecontrol = tune.control(sampling = "cross")) and here i got the mentioned error. can a...

...t of mod is itself an object, and so my statement holds true. Saving a workspace saves all the objects (possibly as references) whether named or not. I was fully aware that the namespace was likely to be up the environment tree of a named object when I chose my words carefully. >> data(BreastCancer) >> >> mod <- bagging(Class ~ Cl.thickness + Cell.size > + + Cell.shape + Marg.adhesion > + + Epith.c.size + Bare.nuclei > + + Bl.cromatin + Normal.nucleoli > + + Mitoses, data=BreastCancer, coob=TRUE) >&g...

...e contained object(s) saved with environment the namespace of ipred - but how would this come about? In this case I think is because the .Rdata file contained an object whose *parent* environment was the namespace of ipred. Take the following example from ?bagging (having loaded ipred): > data(BreastCancer) > > mod <- bagging(Class ~ Cl.thickness + Cell.size + + Cell.shape + Marg.adhesion + + Epith.c.size + Bare.nuclei + + Bl.cromatin + Normal.nucleoli + + Mitoses, data=BreastCancer, coob=TRUE) > > environment(mod$m...

...e contained object(s) saved with environment the namespace of ipred - but how would this come about? In this case I think is because the .Rdata file contained an object whose *parent* environment was the namespace of ipred. Take the following example from ?bagging (having loaded ipred): > data(BreastCancer) > > mod <- bagging(Class ~ Cl.thickness + Cell.size + + Cell.shape + Marg.adhesion + + Epith.c.size + Bare.nuclei + + Bl.cromatin + Normal.nucleoli + + Mitoses, data=BreastCancer, coob=TRUE) > > environment(mod$m...

...pport Vector Machines , Report No.78 (Nov.2002), i am newly working with R but i am not sure how it is handling missing values in the benchmark datasets, I would be very thankful to you if you could let me know how to handle those missing numerical & categorical variables in the data (e.g. BreastCancer). because, i am getting fewer predictions after trained model than the test observations for SVM, so could not calculate confusion matrix. At the same time, function lda(),fda() , rpart() did give the equal predictions. Then i m confused a lot, how these functions handled the missing values, a...