similar to: Arules - Association Rules

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

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

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,

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'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)

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

Hello. I have a general question regarding to clustering of association rules. According to http://cran.r-project.org/web/packages/arules/vignettes/arules.pdf "4.7 Distance based clustering transactions and associations" there is possibility for creating clusters of association rules. I do not understand, how I have to interpret clusters of rules. Let us have next association rules and

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 have a data in the following form : CIN TRN_TYP 9079954 1 9079954 2 9079954 3 9079954 4 9079954 5 9079954 4 9079954 5 9079954 6 9079954 7 9079954 8 9079954 9 9079954 9 . . . . . . there are 100 types of CIN (9079954,12441087,15246633,...) and respective TRN_TYP first of all, I want this data to be

I have a dataframe object having the following structure FinalOutput[1:3,] GasDays 2011-03-31 2010-09-30 2010-10-31 2010-11-30 2010-12-31 2011-01-31 2011-02-28 1 2006-10-01 217303553 221205033 222824639 217016511 216093460 216477468 216834021 2 2006-10-02 231158527 234565250 236004109 231467851 230100639 230079907 230734064 3 2006-10-03 282062314 285427832 286372163

Hello All, I have a dataset and I wish to obtain all possible data cuboids from it using R . For eg if my data frame is : A B C 1 1 1 1 2 1 2 2 1 The output intended is : A=1 A=2 B=1 B=2 C=1 A=1,B=1 A=1,B=2 A=2,B=2 A=1,C=1 A=2,C=1 B=1,C=1 B=2,C=1 A=1,B=1,C=1 A=1,B=2,C=1 A=2,B=2,C=1 Are there any function(s) to do this in R ? I tried a combination of expand.grid and

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 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 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, 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

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

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 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

This is a Request For Comment, also BCCed to 390 package maintainers of reverse dependencies of the Matrix package. Most users and package authors working with our 'Matrix' package will be using it for numerical computations, and so will be using "dMatrix" (d : double precision) matrix objects M, and indirectly, e.g., for M >= c will also use "lMatrix" (l: