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Mining Quantitative Associations
- Techniques can be categorized by how numerical attributes, such as age or salary are treated
- Static discretization based on predefined concept hierarchies (data cube methods)
- Dynamic discretization based on data distribution (quantitative rules, e.g., Agrawal & Srikant@SIGMOD96)
- Clustering: Distance-based association (e.g., Yang & Miller@SIGMOD97)
- One dimensional clustering then association
- Deviation: (such as Aumann and Lindell@KDD99)
- Sex = female => Wage: mean=$7/hr (overall mean = $9)
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