1) Print out the top 10 rules sorted by support:
R> top.support <- sort(rules, decreasing = TRUE, na.last = NA, by = "support")
R> inspect(head(top.support, 10)) # or inspect(sort(top.support)[1:10])
lhs rhs support confidence lift
1 {} => {capital-loss=None} 0.9533 0.9533 1.0000
2 {} => {capital-gain=None} 0.9174 0.9174 1.0000
3 {} => {native-country=United-States} 0.8974 0.8974 1.0000
4 {capital-gain=None} => {capital-loss=None} 0.8707 0.9491 0.9956
5 {capital-loss=None} => {capital-gain=None} 0.8707 0.9133 0.9956
...
2) Print out the top 10 rules sorted by confidence:
R> top.confidence <- sort(rules, decreasing = TRUE, na.last = NA, by = "confidence")
R> inspect(head(top.confidence, 10))
lhs rhs support confidence lift
1 {hours-per-week=Full-time} => {capital-loss=None} 0.5607 0.9583 1.0052
2 {workclass=Private} => {capital-loss=None} 0.6640 0.9565 1.0034
3 {workclass=Private,
native-country=United-States} => {capital-loss=None} 0.5897 0.9555 1.0023
4 {capital-gain=None,
hours-per-week=Full-time} => {capital-loss=None} 0.5192 0.9551 1.0019
5 {workclass=Private,
race=White} => {capital-loss=None} 0.5675 0.9550 1.0018
...
3)
R> rules2 <- apriori(Adult, parameter=list(supp = 0.1, conf = 0.8),
appearance = list(lhs = c("income=small", "income=large"),
default = "rhs"))
R> top.lift <- sort(rules2, decreasing = TRUE, na.last = NA, by = "lift")
R> inspect(head(subset(top.lift, lhs %pin% "income"), 10))
lhs rhs support confidence lift
1 {income=large} => {marital-status=Married-civ-spouse} 0.1370 0.8535 1.8627
2 {income=large} => {sex=Male} 0.1364 0.8496 1.2710
3 {income=large} => {race=White} 0.1457 0.9077 1.0615
4 {income=small} => {capital-gain=None} 0.4849 0.9581 1.0444
5 {income=large} => {native-country=United-States} 0.1468 0.9146 1.0191
...