search for: evaluate_weka_classifier

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 train our data,and some parts to do test,but it should be using in t...

...ndices <- c(1:150)[-(trainingIndices)] testSet <- iris[testIndices,] trainingSet <- iris[trainingIndices,] t <- J48(trainingSet ~ ., data=trainingSet) So far, so good. I can even do predict(t, testSet). Now I want to get more detailed statistics about the performance of my classifier. evaluate_Weka_classifier(t, testSet) This is when I get Error in model.frame.default(formula = trainingSet$Species ~ ., data = list( : variable lengths differ (found for 'Sepal.Length') traceback() returns: 7: model.frame.default(formula = trainingSet$Species ~ ., data = list( [...] 3L, 3L, 3L, 3L, 3L...

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 preditors) > m<-J48(Species~., data=iris) > e <- eval...

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 notic...

Hi, Does anyone know what the negative indexing of a matrix mean? I am using the RWeka and this evaluate classifier does not work on new data like this e <- evaluate_Weka_classifier(m1235,newdata=XW4, complexity = FALSE,class = FALSE) while it work with negative indexing: e <- evaluate_Weka_classifier(m1235,newdata=XW4[,-2], complexity = FALSE,class = FALSE) Although I do not understand what negative indexing of a matrix means, or whether it produces any transf...

Hi, Does anyone know what the negative indexing of a matrix mean? I am using the RWeka and this evaluate classifier does not work on new data like this e <- evaluate_Weka_classifier(m1235,newdata=XW4, complexity = FALSE,class = FALSE) while it work with negative indexing: e <- evaluate_Weka_classifier(m1235,newdata=XW4[,-2], complexity = FALSE,class = FALSE) Although I do not understand what negative indexing of a matrix means, or whether it produces any transf...

...ecision tree: Here is the code: #================== library(RWeka) library(FSelector) library(rpart) data(iris) evaluator <- function(subset) { p <- J48(as.simple.formula(subset, "Species"), data=iris) e <- evaluate_Weka_classifier(p) print(subset) print(e$details[1]) return(e$details[1]) } subset <- forward.search(names(iris)[-5], evaluator) ========================= I got this error, when I ran it: Error in paste(attributes, sep = "", collapse = " + ") : cannot coerce type 'closure' to...

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

...ry(Site) A B C D E F 265 190 260 344 329 198 > m <- JRip(Site~.,data=q) > m JRIP rules: =========== (Dinosaur = TRex) => Site=A (3.0/0.0) => Site=B (5.0/2.0) Number of Rules : 2 > summary(m) Error in evaluate_Weka_classifier(object, ...) : Cannot set dimnames on degenerate confusion matrix. _________________________________________________________________ Hotmail is redefining busy with tools for the New Busy. Get more from your inbox. N:WL:en-US:WM_HMP:042010_2 [[alternative HTML version deleted]]

...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), ncol = 2), numFolds = 10, complexity = TRUE, seed = 123, class = TRUE) e summary(e) e$details ============ But executing "J48(play~., data = w)" generates the following error: ====== Error in .jnew("weka/core/Attribute", attname[i], .jcast(levels,...