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 grouped into basket format:
9079954 1, 2, 3, 4, 5, ....
12441087 19, 14, 21, 3, 7, ...
.
.
.
and then apply eclat from arules package to find frequent patterns.
1) I ran the following code:
file<-read.csv("D:/R/Practice/Data_Input_NUM.csv")
file <- file[!duplicated(file),]
eclat(split(file$TRN_TYP,file$CIN))
but it gave me the following error:
Error in asMethod(object) : can not coerce list with transactions with
duplicated items
2) I ran this code:
file<-read.csv("D:/R/Practice/Data_Input_NUM.csv")
file_new<-file[,c(3,6)] # because my file Data_Input_NUM has many other
columns as well, so I selecting only CIN and TRN_TYP
file_new <- file_new[!duplicated(file_new),]
eclat(split(file_new$TRN_TYP,file_new$CIN))
but again:
Error in eclat(split(file_new$TRN_TYP, file_new$CIN)) :
internal error in trio library
PLEASE HELP
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