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This dataset represents customer transaction records. Each r…

This dataset represents customer transaction records. Each row corresponds to a single transaction, and each column indicates whether a specific item was included in that transaction. The data is presented in binary form: a value of 1 means the item was purchased, while a value of 0 means it was not. 1. Remove the first column (transaction ID) and convert the data to a matrix. Then convert the binary incidence matrix into a transactions database suitable for association rule mining. Create a frequency plot of the items purchased.  (5 pts) 2. Generate an association rule to the data to find all the rules that result in Milk. Set the parameter for supp=0.03, conf=0.8, target=“rules”. Name these as rules1. Explain the first rule in rules1 in your own words. (5 pts)