similar to: Event sequence analysis

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

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"

Dear All, I'd like to use Weka functions that are not implemented (do not have interface) in RWeka, like the Remove function and others in the future! The .java() functionality is for that purpose but I haven't seen any example with Weka functions. Could anyone give me hand in how to do it? For instace if I want to use the weka.filters.unsupervised.attribute.Remove? 1. in the R console,

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

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

Hola, mi nombre es Carla y trabajo en Estadística. Soy nueva en R y estoy haciendo un curso para principiantes. Tengo unos datos de trayectorias de pacientes de un hospital -categorías cualitativas- y quisiera graficar cada trayectoria empleando paletas de colores, para prescindir del texto. Adjunto imagen de trabajo realizado en R para un estudio longitudinal, que se acerca a lo que quisiera

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

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

I am familiar with the rpart and tree packages for classification and regression trees. However, quite a bit of the research in the transportation community relating to decision trees uses the C4.5 family of algorithms by Quinlan. Are there any plans to make a C4.5 (or a derivative of it) available to R? If not, then I might use the WEKA Java package ( http://www.cs.waikato.ac.nz/ml/weka) that

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 =

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, 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

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

I was wondering if R had a data mining componant and how i could get it. If not do you know anyone who is developing a datamining "plug in" for R Phillip Goodreid -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"

Hello, I have a trained Back Propagation Neural Network model in weka. I would like to re-evaluate the NN using R with a given input. How can I do this? I could not find an example of RWeca that applies to NN Thanks, Rui

Hi, guys: These days I keep using R and Weka to do data mining. I think my next step is open the source codes so that I can "customrize them" and make them better server my purpose. But now I kinda hesitate to do so b/c I am really not sure which is better to start with. You know, both require some time and I cannot clone myself to work on both:) If here are some persons who used both

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

Hello: I´m trying to execute Apriori(file.arff) command of RWeka package. I´m working with: Operating System: Windows XP home R-2.4.0 RWeka_0.2-11 rJava_0.4-11 classpath= .;C:\Archivos de programa\Java\jdk1.5.0\lib;C:\Archivos de programa\R\R- 2.4.0\library\RWeka\jar An error occurs when .jnew command is executed, on class "weka/core/Instances" :

I have a data with the sequence of events with millions records and more than 24 time stamped variables. sample data: 1 2 3 4 5 6 7 8 9 10 A A A C C C B B D D D D D D D C C C C C B B A C A C C C D D I want to predict sequence for next 3 period. How this can be achieved using R. Is there any package/function in R do this. I have gone through the document for package "TraMineR" but not

When I perform a rsync with backup I get 100's of: make_bak_dir mkdir "/export/giger.back.....eary/java/weka/gui" failed: File exists make_bak_dir mkdir "/export/giger.back....ary/java/weka/gui" failed: File exists make_bak_dir mkdir "/export/giger.back...ary/java/weka/gui" failed: File exists . . . My backup command is: rsync -q --backup