arules

This question already has answers here : How to prep transaction data into basket for arules (2 answers) Closed 3 years ago . I have a subset from a database in csv which has several different columns and I would like to convert the data into transactions. I've already read this post library(arules) library(arulesViz) trans = read.transactions("data.csv", format = "single", sep = ",", cols = c("EMAIL", "BRAND")) However wasn't able to convert my data with the proposed solution: CATEGORY BRAND SKU EMAIL SEGMENT SALES shorts gap 1564 one@mail.x 1 1 tops gap 8974 one@mail.x 1 2 shoes nike 3245

I'm having troubles with the arulesSequences library in R I have a transactional dataset with temporal information (here, let's use the default zaki dataset). I use SPADE ( cspade function) to find the frequent subsequences in the dataset. library(arulesSequences) data(zaki) frequent_sequences <- cspade(zaki, parameter=list(support=0.5)) Now, what I want is to find, for each sequence (i.e. for each custumer) which are the frequent subsequences that it supports. I tried various combinations of %in% and subset without much success. For example for the second custumer, the initial transactions

I'm using the R package arules . I have some transactions and a rule (see below). I want the subset of transactions that break the rule. How can I do that? This is the set up: library(arules) data(Adult) summary(Adult) rules = apriori(Adult,parameter=list(support=0.2,confidence=0.8)) summary(rules) r=rules[1] I want the subset of transactions that contain the left hand side of the rule r but not the right hand side. The arules documentation doesn't have an example like this. I've tried %in% , match and subset but I can't get the syntax right. The documentation for the subset function has an

When doing frequent sequence mining, one typically wants to the following tasks: 1. Find sequential patterns (frequent sequences). 2. Find out which sequential patterns apply to a transaction. I.e.: given a transaction, which of all of the frequent sequences found is present? I'am having trouble doing the latter. Using R, I am applying the cspade-algorithm from the arulesSequences package on the following toy dataset: data <- data.frame(id = 1:10, transaction = c("A B B A", "A B C B D C B B B F A", "A A B", "B A B A", "A B B B B", "A A A B", "A B B A B B", "E F F A C B D A B C D E", "A B B A B

I'm working with some large transactions data. I've been using read.transactions and apriori (parts of the arules package) to mine for frequent item pairings. My problem is this: when rules are generated (using "inspect()") I can easily view them in the R console. Right now I'm manually copying the results into a text file, then saving and opening in excel. I'd like to just save the generated rules using write.csv, or something similar, but when I try, I receive an error that the data cannot be coerced into data.frame. Does anyone have experience doing this successfully in R? I know I'm

R Basket analysis using arules package with unique order number but duplicate order combinations Just learning R. I'm trying to do a basket analysis using the arules package (but I'm totally open to any other package suggestions!) to compare all possible combinations of 6 different item types being purchased. My original data set looked like this: OrderNo, ItemType, ItemCount 111, Health, 1 111, Leisure, 2 111, Sports, 1 222, Health, 3 333, Food, 7 333, Clothing, 1 444, Clothing, 2 444, Health, 1 444, Accessories, 2 . . . the list goes on and has about 3,000 observations. I collapsed the data

I am trying to load a dataset into R using the data() function. It works fine when I use the dataset name (e.g. data(Titanic) or data("Titanic") ). What doesn't work for me is loading a dataset using a variable instead of its name. For example: # This works fine: > data(Titanic) # This works fine as well: > data("Titanic") # This doesn't work: > myvar <- Titanic > data(myvar) **Warning message: In data(myvar) : data set ‘myvar’ not found** Why is R looking for a dataset named "myvar" since it is not quoted? And since this is the default behavior, isn't there a way to load a dataset stored in a