• Market basket analysis is an analysis conducted to determine which products the customer purchases together.
• Market basket analysis is a mathematical modeling technique based upon the theory that if u buy a certain group of items you are likely to buy another group of items.
• Frequent item set mining leads to the discovery of associations and correlations among items in large transactional or relational data sets.
• With massive amounts of data continuously being collected and stored, many industries are becoming interested in mining such patterns from their databases.
• The discovery of interesting correlation relationships among huge amounts of business transaction records can help in many business decision-making processes.
• A typical example of frequent item set mining is market basket analysis.
• This process analyzes customer buying habits by finding associations between the different items that customers place in their “shopping baskets”
• The discovery of such associations can help retailers develop marketing strategies by gaining insight into which items are frequently purchased together by customers.
• market basket analysis may help you design different store layouts.
• In one strategy, items that are frequently purchased together can be placed in proximity in order to further encourage the sale of such items together.
• In an alternative strategy, placing hardware and software at opposite ends of the store may entice customers who purchase such items to pick up other items along the way
• Market basket analysis can also help retailers plan which items to put on sale at reduced prices.

Eg:

FREQUENT ITEMSET

Given a support threshold of 3 frequent itemsets are :