Displaying 20 results from an estimated 5000 matches similar to: "Extract naiveBayes details"
2012 Feb 07
2
predict.naiveBayes() bug in e1071 package
Hi,
I'm currently using the R package e1071 to train naive bayes
classifiers and came across a bug: When the posterior probabilities of
all classes are small, the result from the predict.naiveBayes function
become NaNs. This is an issue with the treatment of the
log-transformed probabilities inside the predict.naiveBayes function.
Here is an example to demonstrate the problem (you might need
2007 Nov 01
1
RWeka and naiveBayes
Hi
I'm trying to use RWeka to use a NaiveBayes Classifier(the Weka
version). However it crashes whenever there is a NA in the class
Gender
Here is the.code I have with d2 as the data frame.
The first call to NB doesn't make R crash but the second call does.
NB <- make_Weka_classifier("weka/classifiers/bayes/NaiveBayesSimple")
d2[,64]<-d2$Gender=="M"
2010 Jun 30
1
help on naivebayes function in R
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);
2007 Aug 22
1
"subscript out of bounds" Error in predict.naivebayes
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
2011 Feb 08
1
Naive Bayes Issue - Can't Predict - Error is "Error in log(sapply(attribs...)
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:
2007 Sep 25
1
10- fold cross validation for naive bayes(e1071)
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,
2009 Feb 19
1
Bug in predict function for naiveBayes?
Dear all,
I tried a simple naive Bayes classification on an artificial dataset, but I
have troubles getting the predict function to work with the type="class"
specification. With type= "raw", it works perfectly, but with type="class" I
get following error :
Error in as.vector(x, mode) : invalid 'mode' argument
Data : mixture.train is a training set with 100
2007 Oct 30
1
NAIVE BAYES with 10-fold cross validation
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"),
2012 Jul 05
1
Different level set when predicting with e1071's Naive Bayes classifier
Hi!
I'm using the Naive Bayes classifier provided by the e1071 package (
http://cran.r-project.org/web/packages/e1071) and I've noticed that the
predict function has a different behavior when the level set of the columns
used for prediction is different from the ones used for fitting. From
inspecting the predict.naiveBayes I came to the conclusion that this is due
to the conversion of
2018 Feb 26
3
Random Seed Location
Hi all,
For some odd reason when running na?ve bayes, k-NN, etc., I get slightly
different results (e.g., error rates, classification probabilities) from run
to run even though I am using the same random seed.
Nothing else (input-wise) is changing, but my results are somewhat different
from run to run. The only randomness should be in the partitioning, and I
have set the seed before this
2010 Aug 30
2
Regarding naive baysian classifier in R
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
2018 Feb 27
0
Random Seed Location
In case you don't get an answer from someone more knowledgeable:
1. I don't know.
2. But it is possible that other packages that are loaded after set.seed()
fool with the RNG.
3. So I would call set.seed just before you invoke each random number
generation to be safe.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking
2012 May 04
1
weird predict function error when I use naive bayes
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<-
2006 Jul 24
2
RandomForest vs. bayes & svm classification performance
Hi
This is a question regarding classification performance using different methods.
So far I've tried NaiveBayes (klaR package), svm (e1071) package and
randomForest (randomForest). What has puzzled me is that randomForest seems to
perform far better (32% classification error) than svm and NaiveBayes, which
have similar classification errors (45%, 48% respectively). A similar
difference in
2010 Nov 03
2
[klaR package] [NaiveBayes] warning message numerical 0 probability
Hi,
I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4.
I compute a model over a 2 classes dataset (composed of 700 examples).
To that aim, I use the function NaiveBayes provided in the package
klaR.
When I then use the prediction function : predict(my_model, new_data).
I get the following warning :
"In FUN(1:747[[747L]], ...) : Numerical 0 probability with
2018 Mar 04
3
Random Seed Location
On Mon, Feb 26, 2018 at 3:25 PM, Gary Black <gwblack001 at sbcglobal.net>
wrote:
(Sorry to be a bit slow responding.)
You have not supplied a complete example, which would be good in this
case because what you are suggesting could be a serious bug in R or a
package. Serious journals require reproducibility these days. For
example, JSS is very clear on this point.
To your question
>
2012 May 05
1
what is Non-numeric argument to mathematical function in prediction ?
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 <-
2007 Jan 19
1
naive bayes help
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 <-
2012 Aug 02
1
Naive Bayes in R
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
2014 Jun 12
1
do.call Error for Function Not Present When Manually Called
Hello,
The e1071 function naiveBayes gives an error when called by do.call, although it doesn't give any error if I call it manually.
Browse[1]> trainParams at classifier
function (x, ...)
UseMethod("naiveBayes")
<environment: namespace:e1071>
Browse[1]> trained <- do.call(trainParams at classifier, paramList)
Error in names(dimnames(tables[[i]])) <- c(Yname,