similar to: what does negative indexing in a matrix mean?

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

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

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

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

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 notice in

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, 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

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, 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

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 have installed rJava as root sudo -i then R CMD javareconf Exit R CMD INSTALL -l /home/itziar/R/x86_64-pc-linux-gnu-library/3.0 rJava_0.9-4.tar.gz And it was correctly installed. But now when launching R I get a segmentation fault (core dumped) Can anyone help, please? Regards, Itziar Frades [[alternative HTML version deleted]]

Hi, I have some problems to configure the xen I''ve installed (3.3.1). The computer is a Intel Core 2 Duo, I''m using Ubuntu 8.10 and have linux in my dom0 and winxp pro in my domU. I have two cores and I''d like to set the affinity of dom0 to cpu0 and domU to cpu1 but I haven''t find the way of making this permanent. I''ve set cpus=1 in the domU config

Dear all, I sample without replacement elements of a vector and generate a new vector: kl<-c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,5,5,5,5,5,6,6,6,6,6,7,7,8,8, 8,8,8,8,8,8,8) the_index<-c(sample(40,35)) for(fs in 1:length(the_index)){if(fs==1){s<-c(kl[the_index[fs]])}else{s<- append(s, kl[the_index[fs]], after = length(s))}} I am running in BATCH mode this script in a

Hello helpful R folks, First off, please forgive my English. Second, I'm new with R, I've searched the archives about subsets, and I haven't found quite the help I need. I'm currently analysing a population survey whose data set has about 15000 households (the rows/observations) and 130 variables (the columns). I've managed to import the set into R as a data.frame called

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),

Is there a function that will allow me to run all model iterations if I specify a full model? I am using information criteria to choose between possible candidate models. I have been writing out all possible model combinations by hand, and I am always worried that I am missing models or have made a mistake somewhere. It is also difficult to alter models if I want to change a term. For example,

Buenas tardes, Estoy precisando generar una nueva variable que contenga el mes en tres letras, por ejemplo: ENE , FEB, MAR , ABR y así sucesivamente a partir de los valores que ahora tengo en el Dataset, que son 1, 2, 3, 4 y así sucesivamente. Entiendo que sería con mutate, pero consulto acerca del comando completo.. Gracias, Jesús _________________ *Jesús MARTÍN FRADE * Skype:

Pido ayuda para calcular el SALDO *DATAFRAME:* ASIENTO FECHA CUENTA CONCEPTO ARS_DEB ARS_HAB SALDO 1 1 2020-01-01 40100006 Asiento de Apertura 0 199517. -199517. 2 231 2020-01-13 40100006 15/01 CH53677071 GALICIA 14054. 0 14054. 3 231 2020-01-13 40100006 20/01 CH22406030 CREDICOO 9458. 0 23511. 4 231 2020-01-13

Tengo que preparar un Dataset que termine siendo un resumen de cuenta contable a partir de los datos del diario contable de una empresa que el script va filtrando cuenta por cuenta. He podido importar los datos con variables: fecha , concepto, valor debe, valor haber y me falta una variable que sea el saldo. Sucede que el saldo se tiene que calcular fila a fila, es decir sumando el valor debe y

Hola, Estoy haciendo un gráfico con: ############################################################################# ## GRAFICO BARRAS : VALORES AL DEBE MENSUALIZADO ggplot(Diario_S2, aes(x=mes_AAA, by = MES , y=ARS_DEB))+ # ASIGNAR VARIABLES geom_bar(stat="identity", width=0.7, # ANCHO BARRAS colour="grey", fill="darkgreen", #