These rules are generated using the apriori function of the arules package. Let's generate the rules for the other dataset this time:
rules2<- apriori(sampdata,parameter = list(sup = 0.45, conf = 0.9, target="rules"));
The following is the output of the preceding command:
We set the threshold for support as 0.45 and the threshold for confidence as 0.9. From the preceding output, we can see that there are about 40 rules generated. We can print them in descending order of their lift ratio using the following code:
inspect(head(sort(rules2, by="lift"),10))
The output is as follows:
From the output, it is clear that whenever the i128 and i141 items co-occur, it is most likely that the i139 item will occur. Additionally, as the lift value is more than two, it further reiterates that the combination is most likely to occur. We can also get the top rules based on the combination of support, confidence, and lift using the quality function:
head(quality(rules2));
The output...