similar to: Decision Trees

Hi All, I am trying to use the C50 package to build classification trees in R. Unfortunately there is not enought documentation around its use. Can anyone explain to me - how to prune the decision trees? Regards, Indrajit [[alternative HTML version deleted]]

Greetings, Does anyone know if the C4.5 algorithm is already implemented in R? If yes, please let me know the package. Thanks. -- View this message in context: http://www.nabble.com/C4.5-implementation-in-R-tp23736785p23736785.html Sent from the R help mailing list archive at Nabble.com.

Hello, I would like to test some learning algorithms (C5.0, or C4.5) using decision trees or neural network. I didn't find anything in the R documentation for functions to apply on datasets (well, English is not my mother tongue and I have some problems to understand some functions descriptions). Does anybody know where I can find anything about that ? Thank you very much, Thomas

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 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,

Dear all, I have a couple of short noob questions for whoever can take them. I'm from a very non-stats background so sorry for offending anybody with stupid questions ! :-) I have been using logistic regression care of glm to analyse a binary dependent variable against a couple of independent variables. All has gone well so far. In my work I have to compare the accuracy of analysis to a C4.5

Hello, exist an implementation of DecisionTree Algorithms C4.5 from Quinlan in R which extract ruleSets for Classification Problems? I found "only" the packages tree and rpart which use other algorithms ! thanks & regards, christian -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

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

I just uploaded two packages to CRAN. shapefiles_0.1.tar.gz - functions to read and write ESRI shapefiles (including dbfs) emme2_0.1.tar.gz - functions to read binary data from an EMME/2 databank data (EMME/2 is a transportation modeling program) Please let me know if you find any bugs or have some suggestions. Thanks. Regards, Benjamin Stabler Transportation Planning Analysis Unit Oregon

I would like to reference array dimensions by name in an apply and a summary function. For example: apply(x, "workers", sum) Is there a better way to do this than creating a new attribute for the array and then creating new methods for apply and summary? I don't want to name the individual elements of each dimension (such as with dimnames) but rather name the dimensions. Thanks

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

I want to run Rcmd BATCH with R_DEFAULT_PACKAGE=base so it doesn't load any packages, but it seems to reject this argument because it does not start with a '-' or '--'. Is there a different argument that will work? Thanks. Benjamin Stabler Transportation Planning Analysis Unit Oregon Department of Transportation 555 13th Street NE, Suite 2 Salem, OR 97301 Ph: 503-986-4104

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

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, My question is about the algorithm used behind decision tree package rpart. It is not clear in the help if the algorithm used is ID3 or C4.5. Someone has any idea? Regards. Sandro. -- View this message in context: http://www.nabble.com/rpart%3A-ID3-or-C4.5--tp19269303p19269303.html Sent from the R devel mailing list archive at Nabble.com.

I understand how R treats NAs but in the situation below it would be nice to have a na.skip argument to paste so it does not convert the NAs to "NA"s and simply skips those elements of the vector for pasting. > x [1] "2.13" "2.3" NA NA "2.83" NA > paste(x, "0", sep="") [1] "2.130" "2.30"

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 am trying to open an existing binary file, seek to a position in the middle, and then write one byte, while keeping the already existing data after that byte. It seems to me that I am unable to open a connection to a binary file in both read and write mode. I can open the "r+b" binary file connection and seek around, but I can't write to the file. And looking at the function