using arules package, 'apriori' returns 'rules' object.
how can make query - exact column item(s) in rules {lhs, rhs} come ?
example:
i've data in tabular manner in file "input.csv" , want associate/interpret returned rule itemsets column headers in file. how can possibly that?
any pointers appreciated. thanks,
a reproducible example:
input.csv
abc,def,ghi,jkl,mno 11,56789,1,0,10 12,57685,0,0,10 11,56789,0,1,11 10,57689,1,0,12 11,56789,0,1,12 10,57685,1,0,12 10,57689,1,0,10 11,56789,0,1,12 11,56789,0,0,10 11,56789,0,0,10 11,56789,0,1,10 11,56789,0,0,10
call apriori :
transactions <- read.transactions("input.csv", format="basket", sep = ',', cols = null, rm.duplicates = true) rules <- apriori(transactions, parameter = list(supp = 0.45, conf = 0.50, target = "rules"))
returned result:
> inspect(rules) lhs rhs support confidence lift 1 {} => {11} 0.6153846 0.6153846 1.000000 2 {} => {56789} 0.6153846 0.6153846 1.000000 3 {} => {1} 0.6153846 0.6153846 1.000000 4 {} => {10} 0.6923077 0.6923077 1.000000 5 {} => {0} 0.9230769 0.9230769 1.000000 6 {11} => {56789} 0.6153846 1.0000000 1.625000 7 {56789} => {11} 0.6153846 1.0000000 1.625000 8 {11} => {0} 0.6153846 1.0000000 1.083333 9 {0} => {11} 0.6153846 0.6666667 1.083333 10 {56789} => {0} 0.6153846 1.0000000 1.083333 11 {0} => {56789} 0.6153846 0.6666667 1.083333 12 {1} => {0} 0.6153846 1.0000000 1.083333 13 {0} => {1} 0.6153846 0.6666667 1.083333 14 {10} => {0} 0.6923077 1.0000000 1.083333 15 {0} => {10} 0.6923077 0.7500000 1.083333 16 {11, 56789} => {0} 0.6153846 1.0000000 1.083333 17 {0, 11} => {56789} 0.6153846 1.0000000 1.625000 18 {0, 56789} => {11} 0.6153846 1.0000000 1.625000
now, want make distinction between items of say, rule no.13
13 {0} => {1} 0.6153846 0.6666667 1.083333
{0} => {1}
means, value of 0
in dimension "ghi"
implies value of 1
in "jkl"
or vice versa ?
so, there way can column name/id of values of itemsets returned in rules object ?
lhs = left hand side, rhs = right hand side
to read lhs => rhs
.
{0} => {1}
means: if transaction contains 0
, has 1
somewhere.
however, you have not preprocessed data appropriately, results meaningless. data not basket
input format me.
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