similar to: Arules - predict function issues - subscript out of bounds

Hi, we noticed there was a error in the "arules" package. After reading the source code, we saw that the Dice similarity index was "miscalculated" in "dissimilarity" function : an copy-paste from Jaccard Index was not corrected (2* a_b_c, ie 2*(a+b+c) in the code instead of 2*a +b + c !!!). After our mail to R-help (21/11/2006), we thought the authors could do

Hi, I recently got a bizarre message when running arules. It just said "Killed" and quit. Anyone know why this might have happened? I am running R on an AWS quad xl ubuntu instance. Here is some information, including dataset size and the parameters: parameter specification: confidence minval smax arem aval originalSupport support minlen maxlen 0.0003581251 0.1 1 none

I am new to R( but quickly being awed by the range of this it can accomplish, you have one more convert to the useR universe). I have successfully implemented the apriori function and are getting great results. My question concerns how to export these results. I have read lots about write.csv functions and exporting data frames and other standard objects. Im having difficulty working with these S4

 Dear R experts   I generated rules using apriori method in arules package. Though I can access rules using %in% function but I am unable to access a specific rule by its unique identifier number. I want to use rule number for further analysis..   Thanking you in advance.   Daniel Amsterdam                                       Send instant messages to your online friends

Buenas tardes, Necesito ayuda con la función inspect() del paquete "arules". Mis comandos son: r1 <- apriori(tran, parameter=list(support=0.012, confidence=0.7)) r1 summary(r1) #todo bien, tengo 5 reglas y todo claro en el resume #pero al pedir inspect(r1) inspect(sort(r1, by = "confidence")) me arroja el error: Error en UseMethod("inspect", x) : no

Hi, I have been able to generate association rules for Market Basket Analysis using the following codes: **************************************************************************** ******************************************* library("arules") rules <- read.csv("write1.csv",na.strings=c(".", "NA", "", "?"),header=TRUE)

Hi All, I use arules library, and try to create an association rules for this transaction file: a,c,f,3,4,5 b,e,1,2,4 a,c,e,f,1,3,4,5 d,5 b,c,e,f,1,2,3,4 a,c,e,f,1,3,4,5 b,c,e,f,1,3,4 b,e,1,2,4 a,c,e,f,1,3,4,5 a,b,c,e,f,1,3,4 a,c,d,f,3,4,5 I want to get the rule such: {c,e,f}=> {3,4,5} I used this command: ar=apriori(tr, parameter=list(support=.4, confidence=0.8, maxlen=11), appearance

hello, I want to perform the Apriori association rules algorithm to my data. The set of data contains missing values and consists in a combination of continuous and categorical variables. After discretizing the continuous variables, I wrote the following instruiction to perform Apriori, but I obtained the following error message: > rules <- apriori(dd_new,parameter=list(supp=0.5, conf=0.9,

Question 2a) I am also working with arules package and I have the following problem let suppose the matrix b like: b<-matrix(c(1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1),nrow=6) rownames(b)=c("T1", "T2", "T3", "T4", "T5", "T6") colnames(b)=c("It1", "It2", "It3", "It4") bt<-as(b,

Hi, I'm trying out the package arules and I'm having a bit of trouble getting my data to work properly. I have a set of transactions with the purchased products but each product could appear in a different column in the data frame. This causes the rules to be built based on the ordering, which is not significant. Here is an example: # # Code: my.df <- data.frame(

Hi everybody, I am using the apriori() fn in the arules package and am encountered an error. rules <- apriori(rdayst,parameter = list(support = 0.01, confidence = 0.6)) "You chose a very low absolute support count of 0. You might run of memory." I assume this is related to the value of .01 specified for the support = argument. If so, what is a safe and reliable max value for

Hi I have a large dataset, containing a wide range of binary variables. I would like first of all to compute a jaccard matrix, then do a PCA on this matrix, so that I finally can do a hierarchical clustering on the principal components. My problem is, that I don't know how to compute the jaccard dissimilarity matrix in R? Which package to use, and so on... Can anybody help me? Alternatively

Hello, I am using the package arules to generate association rules. I would like to restrict the rules so that in the left-hand side there's only one particular element, let's call it "potatoe". If I do this: rules <- apriori(dtm.mat, parameter = list(sup = 0.4, conf = 0.9,target="rules"), appearance = list(lhs = c("potatoe"))) I get "potatoe"

Hi All Hoping someone can help me with the "transactions" object. I am struggling to get my data in. I know the answer is in the help somewhere I'm sure, I just cannot find it. Essentially, I have data in this format (though I can change it if it particularly unsuitable) Transaction_id, store , salesman, date_time , items 1 , waterfront, john ,

Dear Collegues, it seems like there is a problem with the image()-method in the package arules. Using an ordninary matrix works fine: image(matrix(rnorm(200), 10, 20), axes = FALSE, col=brewer.pal(9, "Blues") ) delivers an image with blue colors and no axes. Using an object of the class "associations" (arules package) does not work: image(items(ta.eclat), axes = FALSE,

I'm using R version 2.13.0 (2011-04-13) on Mac OS X and I get the following error message with library(arules): Loading required package: Matrix Loading required package: lattice Attaching package: 'Matrix' The following object(s) are masked from 'package:base': det Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared object

Dear All, I get some problems using the 'phylo' and dissimilarity functions in R. I converted an output from 'hclust' into an order of phylo so as to be able to use the 'consensus' function on it. Each time I submit the consensus codes, my computer hangs. When I tried to see what the contents of the object converted into order phylo is, I get the message

Hello, I'm using the eclat function of the arules package (1.0-6) for the identification of frequent itemsets. I need the tidLists, but if I set in the function tidLists=TRUE R crashes (Windows XP Professional SP3, 32 bit, R version 2.12.1 (2010-12-16), reproducible on two different computers) with two different error messages or non at all. Minimum examples are: library(arules)

So there are a couple parts to this question. I am trying to implement the rpart/random forest algorithms on a transaction lists. That is to say i am trying to train models in order to deduce what are the most predictive transactions within a customers history in order apply this model to future test data and identify accounting irregularities(ie. this account had x and y so they should have also

Dear R experts,   I need help to make my little program efficient which now takes 2hrs to complete.   Using arules package I developed set of rules consisted of 900 rules. Now I want to check whether a lower rule is a subset of a higher premises rule. And if it is a subset of higher premises rule then drop this rule. I am using following code but it takes too much time.      nor<-length(rules)