In order to perform Apriori analysis, we need to load the arules package. If the package has not been installed, use the install.packages function.
We can then apply the Apriori algorithm on the transactional data. In the previous section we created two different transactional datasets. Let's apply the Apriori algorithm on this dataset:
rules1<- apriori(Adult,parameter = list(sup = 0.5, conf = 0.9,target="rules"));
The output is as follows:
From the preceding output, we can see that there are 52 rules in total that are generated. In the preceding function, we use a few additional sup and conf parameters, which are nothing but support and confidence, respectively. We will explore these parameters in detail but, for now, we have the rules generated based on the inputs. We can then inspect the rules generated using the inspect function as follows:
inspect(rules1)
The following is the output:
The output is continued here:
