similar to: Usage of rJava (.jcall) with Weka functions, any example?

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"

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

Dear all, I wonder which R algorithm could perform a mountain clustering in an spatial grid, in other words, having the coordinates of a map (x,y ... or even more) and then the altitude/height at each point I would like to localise the peaks of that topological surface. Which R algorithm can perform this? I see it as a clustering problem where the peak should be at the center of each cluster.

R experts, I have three columns. c1 and c2 are numeric variables whereas c3 are the clusters classes (nominal variable, 10 different: cluster1, cluster2, cluster3, cluster4, cluster5 ....). I'd like to plot c1 against c2 (easy!) in a 2D plot and put different color depending to the cluster class automatically regardless the number of clusters. Could anyone give a hand? Josep Maria, matrix

Dear List, I´m trying to implement the functionalities from WEKA into my modeling project in R through the RWeka package. In this context I have a slightly special question about the filters implemented in WEKA. I want to convert nominal attributes with k values into k binary attributes through the NominalToBinary filter ("weka.filters.supervised.attribute.NominalToBinary"). But

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

Dear all, I wonder which R algorithm could perform a search of local maxima in an spatial grid, in other words, having the coordinates of a map (x,y,z... up to 6 coordinates) and then the altitude/height at each point (h) (in total 7 numerical variables) I would like to localise the peaks (local maxima) of that topological surface. Which R algorithm can perform this? Thanks a lot, Josep Maria,

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

Hello All, I am trying to carry out variable reduction. I do not have information about the dependent variable, and have only the X variables as it were. In selecting variables I wish to keep, I have considered the following criteria. 1) Percentage of missing value in each column/variable 2) Variance of each variable, with a cut-off value. I recently came across Weka and found that there is an

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, I never use cobweb before and I'm quite new to this. I have a couple of questions around the cobweb implementation in R Weka. If you could supply answer or insight, I would really appreciate. 1. From Fisher's paper in 1987, it seems that Cobweb only deals with nominal data. In R Weka cobweb, is it allowed to accommodate real/continuous value? 2. My understanding is that Cobweb

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,

Howdy Gurus again Thanks to Tony.Breyal, I was able to writing the following script for analyzing a text document. But I got an error with "tm' package. I don't why I got the error from the R script below. I think I followed proccess of R tm manual. I use R v2.8.1. and tm_0.3-3.zip under Win XP. Thanks in advance, Kum Hwang > # setting directory > my.path

Hi, I'm trying to use Information Gain for feature selection. There is a InfoGain implementation in Weka: *weka.attributeSelection.InfoGainAttributeEval* Is it possible to use this function with RWeka? If yes how? list_Weka_interfaces doesn't show it and there is no make function for AttributeEvaluators. Is there any other implementation of InformationGain in R? Thank you Michael

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

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 =

Dear all, I get the error when I use maxent.jar: Error .jcall(mxe, "S", "fit", c("autorun", "-e", afn, "-o", dirout, : java.lang.NoSuchMethodError: density.Params.readFromArgs([Ljava/lang/String;)Ljava/lang/String; sessionInfo() result: R version 2.14.0 (2011-10-31)Platform: i386-pc-mingw32/i386 (32-bit)locale:[1]

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

Dear all, I have some troubles using the stemming algorithm provided by the tm (text mining) + Snowball packages. Here is my config: MacOS 10.5 R 2.12.0 / R 2.13.1 / R 2.14.1 (I have tried several versions) I have installed all the needed packages (tm, rJava, rWeka, Snowball) + dependencies. I have desactivated AWT (like written in

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