Determine the itemsets that has minimum support of 0.03 -

Assignment Detail:- Association Rule Learning 1-1 Loading and Transforming the "grocery transactions-txt" dataset From vUWS, download the "grocery transactions-txt" dataset via: Learning Modules → Week 13 - Association Rule Learning → Practical → grocery transactions, and then load transform it into one-hot encoded format and then load as a Pandas Dataframe- -Hint: for this part, you may use the following code or modify as you see ????t:-grocery items = set-- with open-"grocery transactions-txt"- as f: reader = csv-reader-f, delimiter=","- for i, line in enumerate-reader-: grocery items-update-line- output list = list-- with open-"grocery transactions-txt"- as f: reader = csv-reader-f, delimiter=","- for i, line in enumerate-reader-: row val = item:0 for item in grocery items row val-update-item:1 for item in line- output list-append-row val- grocery = pd-DataFrame-output list- grocery-head-- 1-2 Using the apriori ClassUsing the mlxtend-frequent patterns under Python as we covered on Week 13's lecture slides, determine the itemsets that has minimum support of 0-03- 1-3 Generating the RulesThen for each of the following items below, if a customer buys some of them in the grocery store, then what other items are they also likely to purchase???? -note: foreach one, please just list one item of you think is the most likely-:citrus fruit;pastry;rolls/buns;root vegetables;sausage;tropical fruit;whipped/sour cream;yogurt; Attachment:- Association Rule Learning-rar
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