Displaying 20 results from an estimated 3000 matches similar to: "Questions on RWeka classifiers"
2007 Nov 27
1
Questions on RWeka classifiers?
Hi,
I am using some classifiers in RWeka packages and met a couple problems.
(1) J48 implements C45 classifier, the C45 should be able to handle missing
values in both training set and test set. But I found the J48
classifier can
not be evaluated on test set with missing values--it just ignore them.
(2) The ensemble classifiers in RWeka such as bagging and boosting: there
is a
2009 Jun 04
1
About classifier in RWeka
Hi everyone,
I have trouble to use RWeka, I tried: (w=weather dataset, all
preditors are nominal)
> m<-J48(play~., data=w)
> e<-evaluate_Weka_classifier(m,cost = matrix(c(0,2,1,0),
+ ncol = 2),numFolds = 10, complexity = TRUE,seed = 123,
+ class = TRUE)
it gives me exactly what I want, but when I tried the same classifier
on the other published data: (iris dataset has all numeric
2007 Jul 11
2
RWeka control parameters classifiers interface
Hello,
I have some trouble in achieving the desired parametrisation
for the weka classifier functions, using the package RWeka.
The problem is, that the functions
result=classifier(formula, data, subset, na.action, control = Weka_control(mycontrol))
do not seem to be manipulated by the mycontrol- arguments
Perhaps this should be resepected via the handlers- argument ,
but the
2009 Dec 02
0
RWeka problem with WrapperSubsetEval
Dear all,
I am trying to construct a wrapper that uses random forest to evaluate
the subsets using RWeka and when I do:
nombi <- make_Weka_filter("weka/attributeSelection/WrapperSubsetEval")
datbin<- nombi(gene ~., data=X1X2X3X4W, control =Weka_control( B =
list("weka.classifiers.trees.RandomForest")))
I also have tried with an other induction algorithm:
2010 Oct 19
0
RWeka - Error in model.frame.default - evaluate_Weka_classifier
Hi,
First of all, I'm a complete rookie to R (~2 weeks). But anyway, I'm
trying to use the RWeka interface for C4.5 (J48) classification.
As a proof of concept I'm using the Iris data set to create a training
set of 30 instances (10 per species) and use the remaining 120
instances as my test set.
This is what I do:
trainingIndices <- rep(1:10, 3) + rep(0:2, each=10) * 50
2012 Feb 09
1
Tr: Re: how to pass weka classifier options with a meta classifier in RWeka?
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
2011 Nov 13
1
libary(Rweka) J48 design tree
Hello everybody
I'm having some difficulties to design the decision tree algorithm J48.
I am using the following code and when I run it gives me the following
message
plot(m1)
Error in plot.Weka_tree(m1) :
Plotting of trees with multi-way splits is currently not implemented.
#The code
library(RWeka)
library(randomForest)
library(party)
if(require(mlbench, quietly = TRUE) &&
2011 Sep 07
1
Fwd: FSelector and RWeka problem
Hi all,
Although I sent the mail to Piotr, the author of FSelector, it should be better to ask here to let others know.
Yanwei
Begin forwarded message:
From: Yanwei Song <yanwei.song@gmail.com>
Date: September 7, 2011 4:41:58 PM EDT
To: p.romanski@stud.elka.pw.edu.pl
Subject: FSelector and RWeka problem
Dear Piotr,
Thanks for developing the FSelector package for us. I'm a new
2008 Oct 16
4
How to save/load RWeka models into/from a file?
Hi,
I want to save a RWeka model into a file, in order to retrive it latter
with a load function.
See this example:
library(RWeka)
NB <- make_Weka_classifier("weka/classifiers/bayes/NaiveBayes")
model<-NB(formula,data=data,...) # does not run but you get the idea
save(model,file="model.dat") # simple save R command
# ...
load("model.dat") # load the model
2010 Aug 04
0
RWeka problem: java.lang.NoSuchMethodError
Hi,
I'm trying to use RWeka and followed the following example from the
RWeka manual.
============
## Use some example data.
w <- read.arff(system.file("arff","weather.nominal.arff",
package = "RWeka"))
## Identify a decision tree.
m <- J48(play~., data = w)
m
## Use 10 fold cross-validation.
e <- evaluate_Weka_classifier(m,
cost = matrix(c(0,2,1,0),
2008 Jun 17
1
Decision Trees RWeka
Hello,
I have a question concerning decision
trees coming from RWeka :
library(RWeka)
m =J48(Species~.,data=iris)
How could such a decision tree be transferred
into a matrix, pretty much in the same fashion,
as it is done by getTree() in library(ofw)
library(ofw)
data(srbct)
attach(srbct)
##ofwCART
learn.cart.keep <- ofw(srbct,
2009 Apr 26
2
RWeka prediction
Dear All,I encountered a problem when I use RWeka for prediction.
Specifically, I use the following:
res=J48(X1~.,data=mydata);
predict(res), #it worked fine
but when I tried to use a different data set,
i.e. predict(res,newdata=mynewdata);
all the predictions I get is 0, which apparently is problematic.
What is weird is, if I use the old data, but use the newdata option,
i.e.
2009 Jun 17
1
RWeka evaluate classifier on test set
Hi everyone,
I have a test set with more than 1000 cases, when I use
evaluate_Weka_classifier(RWeka)to evaluate my classifier on this test
set, the output shows me the result of only 83 cases. I do have
missing values in predictors, so I tried na.acton=na.pass, but it
dosen't help. Now I confused, why RWeka ignore so many cases in my
test set? Is there any setting I didn't notice in
2013 Mar 13
1
Accuracy of some classifiers
I am using machine learning for one researching. I am using some
classifiers with 5-fold CV . I would like to know how it is possible to
extract the accuracy, for example, for KNN,neural networks and J48, for
each one of 5-fold because when I apply CV to my classifier, I obtain the
"mean accuracy" of 5-fold but each accuracy/error of each fold is not
returned.
Any help is welcome and
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"
2008 Sep 26
1
RWeka on R-2.7.2___Can't evaluate classifier on test set
Hi, Everyone,
I just installed R-2.7.2 on my computer and then installed package RWeka, version 0.3-13. I noticed that when using command "evaluate_Weka_Classifier", with parameter "newdata=", it still evaluated on training data. Does anyone else noticed this?
My older version of R-2.6.1 with RWeka 0.3-9 worked fine on the same computer.
Bin
2007 Aug 01
1
RWeka cross-validation and Weka_control Parametrization
Hello,
I have two questions concerning the RWeka package:
1.) First question:
How can one perform a cross validation, -say 10fold- for a given data set and given model ?
2.) Second question
What is the correct syntax for the parametrization of e.g. Kernel classifiers interface
m1 <- SMO(Species ~ ., data = iris, control =
2012 Nov 12
0
Weka on command line c.f. using RWeka
Running Weka's command line with calls to system(), like this
> system("java weka.classifiers.bayes.NaiveBayes -K -t HWlrTrain.arff -o")
=== Confusion Matrix ===
a b <-- classified as
3518 597 | a = NoSpray
644 926 | b = Spray
=== Stratified cross-validation ===
=== Confusion Matrix ===
a b <-- classified as
3512 603 | a = NoSpray
2011 Feb 21
1
J48 / Transform from numeric to nominal
Hi everyone,
I am new to field of data mining as well as particularly using R respectively RWeka for writing my master thesis.
I intend to create some specific J48 classification trees with the RWeka_classifiers_tree function. When I run the source code it says ?cannot handle numeric class?. I therefore checked the arff-file and indeed there it says that the class variable is numeric although it
2012 Feb 24
0
RBFNetwork in RWeka
Dear Forum,
I have installed and used various Weka functions in R - both already
available interfaces or created ones via make_Weka_classifier - without any
trouble. However, the RBFNetwork (RBF Neural Network) function is one that I
have not been able to call. I tried creating the R interface using RBF<-
make_Weka_classifier("weka/classifiers/functions/RBFNetwork"), and the