similar to: libary(Rweka) J48 design tree

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 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

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 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 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.

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

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

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, 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

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 hope this formatting is correct as it is my first time. I am trying to do comparisons of values in a data frame that has some factor variables. One instance is > train$sex[2] [1] Male Levels: Female Male So the value is Male but a comparison like "Male" == train$sex[2] will always return FALSE because of the level information included. Another problem this creates is

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 everybody. I'm trying to send the result of a decision tree for latex, but I do not get with the package(xtable), there is a package that make this export Export this for latex marital.status = Divorced | educational.num <= 12: <=50K (1795.0/90.0) | educational.num > 12 | | hours.per.week <= 41: <=50K (302.0/58.0) | | hours.per.week > 41 | | |

Hi, Being a novice this is my first usage of R. I am trying to use rpart for building a decision tree in R. And I have the following dataframe Outlook Temp Humidity Windy Class Sunny 75 70 Yes Play Sunny 80 90 Yes Don't Play Sunny 85 85 No Don't Play Sunny 72 95 No Don't Play Sunny 69 70 No Play Overcast 72 90 Yes Play Overcast 83 78 No Play Overcast 64 65 Yes Play Overcast 81 75

Hi all, I have a package that is specific to a task I was repetitively using a few years ago. I now needed to run it again with new data. However I am told it was built with an older version or R and will not work. How can I tweak the package so it will run on 11.1? It was a one-off product and has not been maintained. Is there a way to "unpackage" it and repackage it to work? I

Quer?a saber si existe alguna funci?n de R para realizar el algoritmo CHAID de ?rbol de clasificaci?n, existen de J48 por ejemplo pero no encuentro nada de este algor?tmo. Muchas gracias y un cordial saludo, Juan -- ========================================================= Juan Antonio Gil Pascual Prof. Titular de M?todos de Investigaci?n en Educaci?n correo: jgil at edu.uned.es web:

Hi, i'm using randomForest package and i have 2 questions: 1. Can i drop one tree from an RF object? 2. i have a 300 trees forest, but when i use the predict function on new data (with predict.all=TRUE) i get only 270 votes. did i do something wrong? Thanks -- View this message in context: http://n4.nabble.com/Random-Forest-tp1557464p1557464.html Sent from the R help mailing list archive at

Good afternoon. I would like to know if there is any function in R to do LOOCV with these classifiers: 1)SVM 2)Neural Networks 3)C4.5 ( J48) 4)KNN Thanks a lot! [[alternative HTML version deleted]]

Dear all, I'm trying to filter out the "number of leaves" (it should be 1 in the example below) from the following string: > string [1] "Java-Object{J48 pruned tree\n------------------\n: 0 (15.0/3.0)\n \nNumber of Leaves : \t1\n\nSize of the tree : \t1\n}" Any idea how to do that as simple as possible? Thanks in advance for any advice. Regards, Andrej

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