similar to: RWeka - Error when attempting to summary() model

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

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 =

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

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

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 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

I'm interested in using R's plotting capabilities to try to generate a graph showing the relationship/pairing frequency of words appearing in a block of unstructured text. I don't have a specific algorithm or approach in mind, just looking to portray text in an interesting fashion. The output I'm hoping for is something like the following called a "Phrase Network":

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

Dear All, I am finding trouble trying to guild a Wrapper using random forest to evaluate the subsets: I do: nombi <- make_Weka_filter("weka/filters/supervised/attribute/AttributeSelection") datbin<- nombi(gene ~., data=X1X2X4X5W, control =Weka_control( S=list("weka.attributeSelection.GeneticSearch"), E=list("weka.attributeSelection.WrapperSubsetEval"),B

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, 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

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 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

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:

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),

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

I am reading dates in Excel2007 into R. Here are the functions I used: library(RODBC) channel<-odbcConnectExcel2007("myfile.xlsx") tmp<-sqlFetch(channel,"1",as.is=T) The dates in myfile.xlsx are all in this format: mm/dd/yyyy. But when I read it to R, some columns look like "yyyy-mm-dd 00:00:00", some columns look like "yyyy-mm-dd", and some

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

Sorry if that's a vague subject, but this problem is a little weird and I'm just wondering if there are any suggestions out there. We've got a Samba server (3.0.23) running on a CentOS 5.3 server offering up a data share of 7TB on an XFS filesystem. The authentication all happens through a Samba PDC with an LDAP backend all on a different server. The system in question is just a

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: