similar to: predictive apriori

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 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 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,

I have a list of data.frames, and i want to iterate over this list and generate graphs with the same title of the data.frame. I did the graphs with: lapply(anual, function(x) plot(x[,'chuva'], type='l', xlab= 'anos', ylab = 'Precicipatação(mm)', col='red')) where anual is list of data.frames. I am plotting just the column "chuva" at each

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, 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'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 help, I am analyzing sequences of events described by time and a unique event tag. And I am searching for recurring patterns where patterns have to show up in a certain time window, e.g. 5 or 10 minutes. Of course, inbetween these events other events may occur. I have applied basket analysis approaches like apriori or 'frequent item set' algorithms with interesting results but

Hello: I´m trying to execute Apriori(file.arff) command of RWeka package. I´m working with: Operating System: Windows XP home R-2.4.0 RWeka_0.2-11 rJava_0.4-11 classpath= .;C:\Archivos de programa\Java\jdk1.5.0\lib;C:\Archivos de programa\R\R- 2.4.0\library\RWeka\jar An error occurs when .jnew command is executed, on class "weka/core/Instances" :

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

 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

Good morning When I try to run an Apriori, I keep often the following message: checking subsets of size 1Error in apriori(tr, parameter = list(supp = 3e-05, conf = 0.05, minlen = 2, : internal error in trio library Other time it works fine on the same data. What can be the reason for this? -- Jolinda Bartlett Eighty20 Consulting Tel: 021 460 0440 Fax: 087 625 0649 3.1 East Wing The Palms

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, 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 ,

Version 1.2.0 of pmml has been released and is available from CRAN. The pmml package (http://rattle.togaware.com/pmml.html) is part of the Rattle data mining suite http://rattle.togaware.com. It generates representations of analytic models built in R using the open standard predictive modelling markup language (http://www.dmg.org/). PMML represents analytic models in an application independent

Version 1.2.0 of pmml has been released and is available from CRAN. The pmml package (http://rattle.togaware.com/pmml.html) is part of the Rattle data mining suite http://rattle.togaware.com. It generates representations of analytic models built in R using the open standard predictive modelling markup language (http://www.dmg.org/). PMML represents analytic models in an application independent

Hi all, I caught a passing reference to PMML on the WEKA list (I think) .. an XML way of communicating 'data mining models'. I am of the opinion that XML is a 'good thing' and I would for instance like to see a standard XML way of communicating the content and context of datasets (eg of timeseries) but it has been a long day and my internet connection is slow and so I have