We can check the details of the rules generated by the cspade function using the following code. The summary function provides you with a highlight about the dataset such as the number of sequences present in the dataset, the most occurring items, frequency table on the length of the sequence, and the distribution of the support measure:
summary(seq_rules)
The output of the preceding command is as follows:
We can take a look at the rules generated by converting them into a data frame using the following code. We can check the various sequences along with the support score for each of them. By default, the rules generated are sorted based on the support score.
as(seq_rules, "data.frame")
The output of the preceding command is as follows:
For details about the plotting of rules, refer to this wonderful blog at http://statistical-research.com/association-rule-learning-and-the-apriori-algorithm/.
For detailed documentation on the packages, refer to the following...