## Why we

- All the methods discussed previously only mine characteristic rules. We sometimes need to find relationships (spatial and non-spatial) between attributes that belong to different classes.

## A spatial association rule is of the form X -->Y (c%), where X and Y are sets of spatial or nonspatial predicates and c% is the confidence of the rule.

## Examples--

- is_a(X,City) and has(X, beach)-->close_to(X, sea) (Spatial RHS)
- Is_a(X, student) --> goes_to(X, school) -- not a spatial association rule.

## Concepts of minimum support and confidence are used to generate rules. Different values at each level .

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