similar to: RWeka control parameters classifiers interface

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 =

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 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

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'm a big fan of both Weka and R (quite new at R :) ), and jumped at the chance to use them together. Unfortunately, I'm running into what is probably a dumb error when trying to view info about my model. A Google search turned up 0 hits for the actual error I got (last line), but you all are smarter! My code is below, but basically my data frame (q) is imported via RODBC and has 1586

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:

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

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, yet another question on S4 method behaviour or rather its side effects: Consider the following example (see below) where a new S4 method 'predict' is defined which by doing so makes 'predict' a S4 standardGeneric. It works and simple test examples run but I'm cautious whether this is a 'silly' thing to do. Is this a dangerous thing to do, already known to

A couple of my functions that were working last week seem to have been changed over the weekend and no longer work, but I can't understand why not: it seems that objects defined at the start of the function are not located further on in the function, when this worked fine before. An example follows at the end, using the package spatstat, though the problem seems more general. My only guess is

Hi! If i found a problem with the code of one of the libraries (not core), or, in my current case, would wish something minor changed for convenience, where can i get contact? Can i put it in the "official" bug repository? (Problem discription for anyone interested: Why call the default function kpca for a matrix with kpar=list(sigma=0.2), instead of putting this default sigma into the

2016-06-27 15:52 GMT+05:00 4lbert C0hen <4lbert.h.c0hen at gmail.com>: > Dear Roman and all, > > Such features would be extremely useful to implement array expansion (scalar > and array renaming, privatization with new subscript expressions of higher > dimension) and storage mapping optimization (generalizing array > contraction). It would be interesting to have these

On 06/28/2016 10:53 AM, Roman Gareev wrote: > 2016-06-27 15:52 GMT+05:00 4lbert C0hen <4lbert.h.c0hen at gmail.com>: >> Dear Roman and all, >> >> Such features would be extremely useful to implement array expansion (scalar >> and array renaming, privatization with new subscript expressions of higher >> dimension) and storage mapping optimization (generalizing

Hi! The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the workspace either. I've tested it with using the matrix version and the

I have a raid-z zfs filesystem with 3 disks. The disk was starting have read and write errors. The disks was so bad that I started to have trans_err. The server lock up and the server was reset. Then now when trying to import the pool the system panic. I installed the last Recommend on my Solaris U3 and also install the last Kernel patch (120011-14). But still when trying to do zpool import

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

Hello Willy, Here is the dump from one of my bitcode files: 0000000 42 43 c0 de 21 0c 00 00 25 05 00 00 0b 82 20 00 As expected, 0x42 (= B), 0x43 (= C), xc0 and 0xde are in correct order. In your case, the first byte is read as 37 (= 0x25). I wonder why? When you check the bytes yourself, you get expected results. When the same bytes are read from Stream object, you get a different result (maybe

dear: when I read a Excel file(exp-11),The R project give me a error ,Just like this: ??'datafile' > write.foreign("exp-11.xls") ???list(df = df, datafile = datafile, codefile = codefile) : ??'datafile' > write.foreign("exp-11.xls") ???list(df = df, datafile = datafile, codefile = codefile) : ??'datafile' >

I am using the package "tm" for text-mining of abstracts and would like to use it to find instances of gene names that may contain white space. For instance "gene regulatory protein 1". The default behavior of tm is to parse this into 4 separate words, but I would like to use the class constructor "dictionary" to define phrases such as just mentioned. Is this

I'd like to propose that the whenever the length of condition passed to an if or a while statement differs from one, an error is produced rather than just a warning as today: > x <- 1:2 > if (x == 1) message("x == 1") x == 1 Warning message: In if (x == 1) message("x == 1") : the condition has length > 1 and only the first element will be used There are