similar to: arules "killed"

Hi, I am using Rattle 2.6.4 with R 2.12.2 on win64, is this a bug ? Following is the content after execute the associate analysis process: Summary of the Apriori Association Rules: Number of Rules: 23351 Summary of the Measures of Interestingness: support confidence lift Min. :0.1250 Min. :1 Min. :2.667 1st Qu.:0.1250 1st Qu.:1 1st Qu.:2.667 Median :0.1250

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,

 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

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, 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 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

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 everyone, This is my first posting and I am just starting to fumble my way thru R. I have been working thru the Arules package, and I used to be able to use the image function and I get the following message: Error in image.default(basket2) : 'z' must be a matrix I used to be able to plot the image. I only started to get this error when I tried to add x and y axis labels.

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 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, there: I have a question on use of arules package: suppose i have a classification problem with class id = 1 or 0. i put predictors and class ids together and tranform all of them into binary thus i got a binary matrix. When I build the rules from it, I subset the rules to 2 by defining rhs %in% "classid = 1" or "2". (Actually i can build rules from two seperate datasets

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, 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 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 ,

Suppose this is my list of transactions: set.seed(200) tran=random.transactions(100,3) inspect(tran) items transactionID 1 {item80} trans1 2 {item8, item20} trans2 3 {item28} trans3 I want to get the 'transpose' of the data, i.e. transactionID items 1 {trans2} item8 2 {trans2} item20 3 {trans3} item28 4 {trans1} item80 I

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

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 Colleagues, I would like to only inspect rules that contain a certain label substring on the rhs. In this special case the item labels are built like this: <itemtype>_<itemvalue> e.g. "Artikelgruppe_E0815" what I want to do is only show rules where "Artikelgruppe" is contained in the rhs - has anybody an idea how this could work? Sincerely

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

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,