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Elucidate Market Basket Analysis with an example.

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Market Basket Analysis (MBA) is a data mining technique used in the field of retail and marketing to uncover associations between products that are frequently purchased together. The fundamental idea behind market basket analysis is to identify patterns of co-occurrence in customer transactions and discover relationships between items.

Key concepts in Market Basket Analysis include:

  1. Association Rules:
    • The primary output of market basket analysis is the discovery of association rules. These rules express relationships between products based on the likelihood that they will be purchased together. A common representation of an association rule is “If A, then B,” where A and B are items.
  2. Support:
    • Support is a measure of how frequently a set of items appears together in the transactions. It is calculated as the number of transactions containing the items divided by the total number of transactions. High support indicates a strong association.
  3. Confidence:
    • Confidence measures the reliability of the association rule. It is calculated as the number of transactions containing both items A and B divided by the number of transactions containing item A. High confidence indicates that when item A is purchased, there is a high probability that item B will also be purchased.
  4. Lift:
    • Lift is a measure of how much more likely item B is to be purchased when item A is purchased, compared to when item B is purchased independently of item A. A lift greater than 1 indicates a positive correlation, suggesting a likely association.

Example: Consider a supermarket transaction dataset:

Transaction  Items
1            {Bread, Milk}
2            {Bread, Diapers, Beer}
3            {Milk, Diapers, Cola}
4            {Bread, Milk, Diapers, Beer}
5            {Bread, Milk, Cola}

Association rules that might be discovered include:

  • {Bread} => {Milk} with high support and confidence.
  • {Diapers, Beer} => {Bread} with moderate support and confidence.
  • {Cola} => {Milk} with low support and confidence.

These rules can provide insights for retailers in terms of product placement, marketing strategies, and recommendations to increase sales. For instance, if a supermarket knows that bread and milk are frequently purchased together, they might place these items closer to each other to encourage additional purchases.

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