similar to: Different level set when predicting with e1071's Naive Bayes classifier

Hey guys, I can't get my Naive Bayes model to predict. Forgive me if its simple... I've tried about everything and can't get it to work. Reproduceable code below. Thank you, Mike -- Michael Schumacher Manager Data & Analytics - ValueClick mike.schumacher@gmail.com * Functional Example Code from UCLA:

I am trying to plot two density lines on the same graph. Using the functions on the base package, I would go: plot(density(x), col = 1) lines(density(y), col = 2) And I get two distinct (one-bump) density lines. When I try to do it using lattice, I get two two-humped lines. (In other words, I think the smoothing function is taking the next set of data points and smoothing them in the same

Hello fellow R programmers, I'm trying to use package e1071's naiveBayes function to create a model with weighted data. See example below, variable "d" is a count variable that provides the # of records for the given observation combination. Is anyone aware of a "weight" argument to this method? I've been unsuccessful in my research. Thanks, Mike

Hallo! I would need a code for 10-fold cross validation for the classifiers Naive Bayes and svm (e1071) package. Has there already been done something like that? I tried to do it myself by applying the tune function first: library(e1071) tune.control <- tune.control(random =F, nrepeat=1, repeat.aggregate=min.,sampling=c("cross"),sampling.aggregate=mean, cross=10, best.model=T,

Hi, I have a small doubt regarding naive Bayes. I am able to classify the data's properly but i am just stuck up with how to get the probability values for naive bayes. In the case of SVM we have "attr" function that helps in displaying the probability values. Is there any function similar to "attr" in naive Bayes that can be used for displaying the attribute values. my

hello, all. in my previous research, i have always used existing data. i am trying something new as an exploratory exercise and have never create my own variable form scratch. essentially, i am creating a variable for party affiliation. here is an example. var =party. levels= democrat, republican, other. respondents will indicate which category they fall under. for the sake of ease, i will

I have the vncserver running on CentOS 4, but when I log in using vncviewer from another box, I don't see my gnome desktop, just a fancy terminal. I suspect I need to edit the ~/.vnc "xstartup file, but what do I add to fix this. On all other distros I have tried, the vncserver serves up my gnome desktop by default. -- Lee Parmeter Emperor, linXos - The Flying Penguin

Hi, I tried to use naivebayes in package 'e1071'. when I use following parameter, only one predictor, there is an error. > m<- naiveBayes(iris[,1], iris[,5]) > table(predict(m, iris[,1]), iris[,5]) Error in log(sapply(attribs, function(v) { : Non-numeric argument to mathematical function However, when I use two predictors, there is not error any more. > m<-

I downloaded and installed apt and synaptic using yum ok, but are there corresponding apt repo's for the yum ones? If so, what are they? -- Lee Parmeter Emperor, linXos - The Flying Penguin http://www.linXos.com Linux Registered User #337161 'It's free. It works. Duh.'" - Eric Harrison The United States is NOT a democracy, it was founded as a Republic! God is not a

I am wondering if anybody here have a simple example in R for Naive Bayes. For example, I can do k-means clustering on the "iris" data - data(iris) cl <- kmeans(iris[,1:4], 3) cl$cluster cbind(1:150,iris$Species) =========== But how to do Naive Bayes classification in the same "iris" data? Many thanks! -- View this message in context:

Hello I have a rather simple code and for some reason it produces an error message. If someone can tell me why and how to fix it, I would be very greatful. Thank you in advance. ##### create data set.seed(10) n <- 200 # number of training points n.test <- 200 # number of test points p<-2 # dimension of input space z <-

hi there!! i am trying to implement the code of the e1071 package for naive bayes, but it doens't really work, any ideas?? i am very glad about any help!! i need a naive bayes with 10-fold cross validation: code: library(e1071) model <- naiveBayes(code ~ ., mydata) tune.control <- tune.control(random = FALSE, nrepeat = 1, repeat.aggregate = min, sampling = c("cross"),

I'm developing a naive bayes in R. I have the following data and am trying to predict on returned (class). dat = data.frame(home=c(0,1,1,0,0), gender=c("M","M","F","M","F"), returned=c(0,0,1,1,0)) str(dat) dat$home <- as.factor(dat$home) dat$returned <- as.factor(dat$returned) library(e1071) m <- naiveBayes(returned ~ ., dat) m

Hi, Currently I testing the packets that contain built-in features for classification. Actually I looked packages such as: e1071, Klar, Caret, CORElearn. However, from what I noticed when building a naive Bayesian classifier, that they package use of the finite mixture model to estimate P (x | C) and using a normal distribution. In my research I use binary data and I want modeled P (x | C), eg the

I'm trying to fit a naive Bayes model and predict on a new data set using the functions naivebayes and predict (package = e1071). R version 2.5.1 on a Linux machine My data set looks like this. "class" is the response and k1 - k3 are the independent variables. All of them are factors. The response has 52 levels and k1 - k3 have 2-6 levels. I have about 9,300 independent variables

I created an account on the Forums this morning, but I got an error saying they were having a problem sending e-mail. I sent a message to the webmaster and no response either. So I can't post to the forum until my account is activated. Are the forums new? By the amount of traffic on the list, this must be where most people resolved their problems. I am thinkgng about installing CentOS 4 on my

I'm trying to figure out how to use lmer to fit models with factors that have some nesting and some non-nested groupings. For example, in this paper: http://www.stat.columbia.edu/~gelman/research/published/parkgelmanbafumi.pdf we have a logistic regression of survey respondents' political preferences (1=Republican, 0=Democrat), regressing on sex, ethnicity, state (51 states within 5

Le jeudi 09 f?vrier 2012 ? 15:31 +0200, Kari Ruohonen a ?crit : > Hi, > I am trying to replicate a training of AttributeSelectedClassifier with > CFsSubsetEval, BestFirst and NaiveBayes that I have initially done with > Weka. Now, I am trying to use RWeka in R. > > I have a problem of passing arguments to the CfsSubsetEval, BestFirst > and NaiveBayes. I have first created an

Hello, First time poster here so let me know if you need any more information. I am trying to run an ordered probit with maximum likelihood model in R with a very simple model (model <- econ3 ~ partyid). Everything looks ok until i try to run the optim() command and that's when I get " Error in rep(1, nrow(x)) : invalid 'times' argument". I had to adapt the code from a 4

Dear r-users, I am looking for an implementation of the Naive Bayes classifier for a multi-class classification problem. I can not even find the Naive Bayes classifier for two classes, though I can not believe it is not available. Can anyone help me? Uschi -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read