similar to: Función Inspect() en "arules" package

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

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

 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

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 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,

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!!!

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 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*

Hola, Quizás no es el ámbito más apropiado, pero vale la pena intentar. ¿Existe alguna implementación en R del modelo de reglas de asociación que pueda realizar el cálculo en paralelo sobre un cluster Hadoop? He visto los paquetes que 'paralelizan' R, pero no mencionan nada acerca de modelos de reglas de asociación. Saludos -- Oscar Benitez [[alternative HTML version deleted]]

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 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 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, 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,

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)

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 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

Junto con saludar, Quer?a saber si los que han usado boxplot.stats, saben como ubicar los resultados que arroja como "out" (outliers) directamente en la base de datos, ya que, muestra los resultados en valor de cada dato at?pico. Por ejemplo, estoy usando una base de datos con 300 datos y 10 columnas, en este caso estoy buscando los datos at?picos de la columna del precio de x

He tratado de usar lo siguiente: a<- ifelse(BD$Divisi?n>=50 & BD$Divisi?n<59,"D", ifelse (BD$Divisi?n>=60 & BD$Divisi?n<=69,"G", ifelse (BD$Divisi?n>=70 & BD$Divisi?n<=79,"L", ifelse (BD$Divisi?n>=80 &

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)