Dear sir,
I have 2 questions:
Question 1:
suppose that we have the following:
a<-matrix(c(0,2,0,4,0,6,5,8,0),nrow=3)
colnames(a)<-c("F1","F2","F3")
rownames(a)<-c("A1","A2","A3")
a
ind <- which(a == 0, arr = TRUE)
mapply("[", dimnames(a), as.data.frame(ind))
I want to add a column to the result. This Column added depends on the 2
first column value of the row. The result should be something like this:
[,1] [,2] [,3]
[1,] "A1" "F1" "A1 excludes F1"
[2,] "A3" "F1" "A3 excludes F1"
[3,] "A2" "F2" "A2 excludes F2"
[4,] "A3" "F3" "A3 excludes F3"
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, "transactions")
rules<-apriori(bt, parameter = list(maxlen=2))
k<-inspect(rules)
k
##we obtain
lhs rhs support confidence lift
1 {} => {It4} 1.0000000 1 1.0
2 {} => {It1} 1.0000000 1 1.0
3 {It3} => {It2} 0.5000000 1 1.5
4 {It3} => {It4} 0.5000000 1 1.0
5 {It3} => {It1} 0.5000000 1 1.0
6 {It2} => {It4} 0.6666667 1 1.0
7 {It2} => {It1} 0.6666667 1 1.0
8 {It4} => {It1} 1.0000000 1 1.0
9 {It1} => {It4} 1.0000000 1 1.0
WRITE(rules)
##we obtain
"rules" "support" "confidence" "lift"
"1" "{} => {It4}" 1 1 1
"2" "{} => {It1}" 1 1 1
"3" "{It3} => {It2}" 0.5 1 1.5
"4" "{It3} => {It4}" 0.5 1 1
"5" "{It3} => {It1}" 0.5 1 1
"6" "{It2} => {It4}" 0.666666666666667 1 1
"7" "{It2} => {It1}" 0.666666666666667 1 1
"8" "{It4} => {It1}" 1 1 1
"9" "{It1} => {It4}" 1 1 1
I want to convert this in a matrix or data frame and the result should be
something like this
##we obtain
rules support confidence lift
1 {}=>{It4} 1.0000000 1 1.0
2 {}=>{It1} 1.0000000 1 1.0
3 {It3}=>{It2} 0.5000000 1 1.5
4 {It3}=>{It4} 0.5000000 1 1.0
5 {It3}=>{It1} 0.5000000 1 1.0
6 {It2}=>{It4} 0.6666667 1 1.0
7 {It2}=>{It1} 0.6666667 1 1.0
8 {It4}=>{It1} 1.0000000 1 1.0
9 {It1}=>{It4} 1.0000000 1 1.0
In another hand is it possible to obtain all the rules where lHS<=>rhs?. In
our last example that means to obtain
lhs rhs support confidence lift
8 {It4} => {It1} 1.0000000 1 1.0
9 {It1} => {It4} 1.0000000 1 1.0
Thanks again Alberto
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