Let’s call the problem “Market Basket Optimization.” Our goal here is to generate a list of sets (product sets) and their corresponding level of relatedness or support to one another. Here’s a peek of the dataset to give you a better idea: shrimp,almonds,avocado,vegetables mix,green grapes,whole wheat flour,yams,cottage cheese,energy drink,tomato juice,low fat yogurt,green tea,honey,salad,mineral water,salmon,antioxidant juice,frozen smoothie,spinach,olive oil burgers,meatballs,eggs chutney turkey,avocado mineral water,milk,energy bar,whole wheat rice,green tea low-fat yogurt whole-wheat pasta,french fries soup,light cream,shallot frozen vegetables,spaghetti,green tea french fries Those are listed according to the transactions where they appear. For example, in the first transaction, the customer bought different things (from shrimp to olive oil). In the second transaction, the customer bought burgers, meatballs, and eggs.
Let’s call the problem
“Market Basket Optimization.” Our goal here is to generate a list of sets (product sets) and their corresponding level of relatedness or support to one another. Here’s a peek of the dataset to give you a better idea:
shrimp,almonds,avocado,vegetables mix,green grapes,whole wheat flour,yams,cottage
cheese,energy drink,tomato juice,low fat yogurt,green tea,honey,salad,mineral
water,salmon,antioxidant juice,frozen smoothie,spinach,olive oil
burgers,meatballs,eggs chutney turkey,avocado mineral water,milk,energy bar,whole wheat rice,green tea low-fat yogurt whole-wheat pasta,french fries
soup,light cream,shallot frozen vegetables,spaghetti,green tea french fries
Those are listed according to the transactions where they appear. For example, in the first transaction, the customer bought different things (from shrimp to olive oil). In the second transaction, the customer bought burgers, meatballs, and eggs.
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