1. Data-mining functions: Here are three examples of data mining applications. Match each application to one of the three data-mining functions. Then, for each particular application, elaborate potential variables (features/attributes), techniques (algorithms/models) and evaluation criteria. [15 points]

1. A credit card company tries to distinguish fraud transactions from thousands of normal transactions.
2. A supermarket analyzes customers transaction records and find out items that are often purchased together.
3. A furniture retailer tries to identify its target customers by segmenting the market into groups of similar people.

Data-mining functions:

Association mining: ( )

• Variables (features/attributes)?
• Techniques (algorithms/models)?
• Evaluation criteria?

Cluster analysis: ( )

• Variables (features/attributes)?
• Techniques (algorithms/models)?
• Evaluation criteria?

Classification: ( )

• Variables (features/attributes)?
• Techniques (algorithms/models)?
• Evaluation criteria?

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