You are given the transaction data shown in the Table below from a fast food restaurant. There are 9 distinct transactions (order:1 - order:9) and each transaction involves between 2 and 4 meal items. There are a total of 5meal items that are involved in the transactions. For simplicity we assign the meal items short names (M1 - M5) rather than the full descriptive names (e.g., Big Mac). For all of the parts below the minimum support is 29(.222) and the minimum confidence is 7/9(.777). Note that you only need to achieve this level, not exceed it. For all of the parts below the minimum support is 2/9(.222) and the minimum confidence is 7/9(.777). Note that you only need to achieve this level, not exceed it. 1. Apply the Apriori algorithm to the dataset of transactions and identify all frequent k-itemsets. Show all of your work. You must show candidates but can cross them off to show the ones that pass the minimum support threshold. Note: if a candidate itemset is pruned because it violates the Apriori property, you must indicate that it fails for this reason and not just because it does not achieve the necessary support count (i.e., in these cases there is no need to actually compute the support count). So, explicitly tag the itemsets that are pruned due to violation of the Apriori property. (If you do not know what the Apriori property is, do not panic. You will ultimately get the exact same answer but will just lose a few points). 2. Find all strong association rules of the form: XYZ and note their confidence values. Hint: . the answer is not 0 so you should have at least one frequent 3-frequent itemset