similar to: How to get rule number in arules

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

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

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

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

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)

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(

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)

Hi, I'm doing a Market Basket Analysis in which I have a list of transaction id's in column 2 and transactions(product names) in column 1. I read this into a transaction file using a txn<-read.transaction(file="data.csv",format='single', rm.duplicates=F, cols=c(1,2)) If I want to use the apriori algorithm everything seems to be running fine. However it is when I want

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

Hello everybody! I'm trying some datamining, but i'm having some problems with arule package, in the end of processing R "had to be closed". I already tryied to reinstall the 2.10 version, change the computer and realocated more virtual memory. Does anyone had this problem to? I had a hiphoteses that i have to prepare the data, somehow i don't know. Thanks for helping!!!

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"

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

Hi, I am having some trouble using R 2.13.1 for generating a pmml object of of class "c('randomForest.formula', 'randomForest')" I see that these methods are available: > methods(pmml) [1] pmml.coxph* pmml.hclust* pmml.itemsets* pmml.kmeans* pmml.ksvm* pmml.lm* pmml.multinom* pmml.nnet* pmml.rpart* [10] pmml.rsf* pmml.rules* pmml.survreg*

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,

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 ,

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,

Dear all, This is the first time I am sending mail to the mailing list, so I hope I do not make a mistake... The last months I have been working on my MSc thesis project on performing data mining techniques on user logs of a software-as-a-service application. The main problem I am experiencing is how to process the huge amount of data. More specifically: I am using R 2.10.1 in a laptop with

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)

Dear R-help, I am looking for ideas and presentations of new and advanced data visualization methods. As an example of what I am searching for, the 'Many Eyes' pages at http://manyeyes.alphaworks.ibm.com/manyeyes/ may provide a good paradigm. I would be interested even if it will not be easy to implement such examples in R, e.g. because of the interactive nature of these graphical