similar to: RWeka on R-2.7.2___Can't 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

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

Hi everyone, I have a question about using RWeka package? we know that instruction make_Weka_classifier that can help us to build a model,and evaluate_Weka_classifier instruction can help us to evaluate the performance of the model using on new data. But I have a question about how to using the parameter numFold in evaluate_Weka_classifier.Cross-validation means that using some parts to

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

Hi, Does anyone know what the negative indexing of a matrix mean? I am using the RWeka and this evaluate classifier does not work on new data like this e <- evaluate_Weka_classifier(m1235,newdata=XW4, complexity = FALSE,class = FALSE) while it work with negative indexing: e <- evaluate_Weka_classifier(m1235,newdata=XW4[,-2], complexity = FALSE,class = FALSE) Although I

Hi, Does anyone know what the negative indexing of a matrix mean? I am using the RWeka and this evaluate classifier does not work on new data like this e <- evaluate_Weka_classifier(m1235,newdata=XW4, complexity = FALSE,class = FALSE) while it work with negative indexing: e <- evaluate_Weka_classifier(m1235,newdata=XW4[,-2], complexity = FALSE,class = FALSE) Although I

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

I'm a big fan of both Weka and R (quite new at R :) ), and jumped at the chance to use them together. Unfortunately, I'm running into what is probably a dumb error when trying to view info about my model. A Google search turned up 0 hits for the actual error I got (last line), but you all are smarter! My code is below, but basically my data frame (q) is imported via RODBC and has 1586

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

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

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

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),

Hi, I downloaded RWeka successfully. (At least I do not see, where I could have made a mistake.) Then I tried to load it by the library-command. To my surprise this did not work. Result: library(RWeka) Fehler in .jinit(c(system.file("jar", "weka.jar", package = "RWeka"), system.file("jar", : Cannot create Java Virtual Machine Fehler: .onLoad in

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

Hi, I have a question about using RWeka Clusterers.If you could supply answer or insight, I would really appreciate it. When I run a simple code which uses a clusterer from RWeka I get an error. the sample codes and errors are mentioned below Code: library(RWeka) Cobweb(iris[,-5],control=NULL) Error: Error in names(class_ids) <- nms : 'names' attribute [150] must be the same

Dear R-users, I am running R 2.10.1 under Windows XP Professional. Moreover, I run Java 5.0 and the RWeka package 0.4-1 and rJava 0.8-4. are successfully installed. I get two error messages while loading both packages. library(RWeka) Error in get(Info[i, 1], envir = env) : internal error -3 in R_decompress1 Error: package/namespace load failed for 'RWeka' 2:

When I sink the output of an RWeka model to a text file, the output file appears empty: library(RWeka) model = LogitBoost(Species~.,data=iris) print(model) sink("output.txt") print(model) #file output.txt is created, but it is blank sink() Am I doing anything wrong? [[alternative HTML version deleted]]

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,

Hi - I have a question on RWeka. I installed the package and try to run using some examples available in the package. However, it stalls my machine for a while. I'm wondering if I need weka (which is java implementation) installed before using RWeka? Thank you. - adschai

Hello all, I am attempting to run an R script that makes use of RWeka. I am running SuSE Linux 9.3 with Java 1.5.0_06, R version 2.2.1, Weka 3-4-7, and Rweka 0.2-1. CLASSPATH="/usr/local/weka-3-4-7/weka.jar:/usr/local/JGR/JGR.jar" I receive the error: NewObject("weka/core/Instances","(Ljava/io/Reader;)V",...) failed Exception in thread "main"