similar to: Regarding naive baysian classifier in R

Dear R users and developers After upgrading to Windows XP and R 1.9.1 and 2.0, I retried to execute plot.baysian() to a data set that I had used previously to plot with no problem in win2000 R1.8. The error I get is: Error in points(Mbar[-index], lods[-index], pch = ".") : only 0's may mix with negative subscripts Thanx in advance Dino P.S. I allready sent this message

HI, List I want to know weather any body has used BMA Package for model averaging for prediction of future values.....What are the paprmeters we have to suplly to the model. Any script for the same. thanks in advance ANIL KUMAR( METEOROLOGIST) LRF SECTION NATIONAL CLIMATE CENTER ADGM(RESEARCH) INDIA METEOROLOGICAL DEPARTMENT SHIVIJI NAGAR PUNE-411005 INDIA MOBILE +919422023277

Hi there, two questions. 1) Is there any possibility to look up the help pages within R for more complex combinations of character strings, for example "Bayesian" AND "regression" but not necessarily "Bayesian regression"? 2) Is there a package/command that does fully Bayesian linear regression (if possible with variable selection)? Thanks, Christian *** --- ***

Hi I am Aadhithya I am trying to write a code to classify microarray data (AML and ALL) using SVM in R my code goes like this : library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); model<- svm(train,cl); pred <-

Hi, I have written a code in R for classifying microarray data using naive bayes, the code is given below: library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); cl <- factor(cl) model <- NaiveBayes(train,cl);

Hi, I have written a code in R for classifying microarray data using naive bayes, the code is given below: library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); cl <- factor(cl) model <- naiveBayes(train,cl);

Hi Thanks for replying my question! What really interested me is that the package providing some complex form sampling, such as wishart, multinomial, dirichlet. And others for example conditional beta distribution confining the random variable in the interval (a, b). Since these concept are widely used in the baysian, I wonder whether somebody has already written this package. Thanks! Best

Dear r-help, I create a graph of my baysian network. I use the package igraph. The names of vertex are within the circle, I would leave them outside the circle? > E(g)$color <- "black" > tkplot(g, ,vertex.label=names,layout=layout.kamada.kawai, edge.color=E(g)$color) Best Regards [[alternative HTML version deleted]]

Hello, Is there any literature there that says that the EM is better/worse than a Baysian model when it comes to differentiating univariate mixture of normal distributions? -- Thanks, Jim. [[alternative HTML version deleted]]

I read through the editorial. This is the one of the most mega-ultra-super-biased articles I've ever read. e.g. The authors encourage Baysian methods, and literally encourage subjective approaches. However, there's only one reference to robust methods and one reference to nonparametric methods, both of which are labelled as purely exploratory methods, which I regard as extremely

Hi folks, A spammer is getting email addresses from the mailing list and sending people an email saying he needs help. This is the classic advance free fraud. This is what he says in broken english - "I need your urgently assistance in transferring the sum of $39.5)million to your account. This fund belongs to our decease costumer who died along with his Family in air crash. Contacts me for

Hello Gurus: When I plot a survival fit using rpart for the classification tree, for each node, there is a decimal based number above the event/total. I tried to see if it's the exponential ratio or logrithmics, neither seem to be the case. I'm wondering if anyone knows what they are. Thanks, Karen _________________________________________________________________ Find hidden words,

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 all, As I have promised I am sending my QoS rules. This now works fine with u32 classifier (and parent 1:0 that I could not understand why it did not worked well before). Att, Nataniel Klug ------------------------ #!/bin/sh #------ # Script de QoS Cyber Nett #------ # Nataniel Klug # suporte@cnett.com.br #------ TC="/sbin/tc" IPT="/usr/local/sbin/iptables"

Hello, I just compiled a new kernel.iptable/iproute2 to fresh up my router. There is a little problem... The fw classifier does not work in tc. I read some note found in the source of iproute2 and it says: "* To use "fw" classifier you will need ipfwchains patch." I can''t find this patch. Do you have it? Is there any other way to implement the "fw"

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

Dear All, I'm currently doing a project about unsupervised learning, and I'll be using R to analyse a few network traffic datasets downloaded off Andrew Moore's website (http://www.cl.cam.ac.uk/Research/SRG/netos/nprobe/data/papers/sigmetrics/index.html). Could anyone shed some light on how to build a classifier from the training set A, and then use a validation set B to assess the

Hi, I have a bunch of data points x from two classes A & B, and I'm creating a classifier. So I have a function f(x) which estimates the probability that x is in class A. (I have an equal number of examples of each, so p(class) = 0.5.) One way of seeing how well this does is to compute the error rate on the test set, i.e. if f(x)>0.5 call it A, and see how many times I

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing