Abstract
The cascade model is a rule induction methodology that uses the level-wise expansion of a lattice. An attribute-value pair is expressed as an item, and every node in the lattice is specified by an itemset and its supporting instances. If the distribution of the class attribute values suddenly changes along a link in the lattice, the link is represented as a rule "IF item-along-link added on itemset-on-upper-node, THEN class-i". The strength of the rule is measured by the BSS value of the link. In the SAR (structure activity relationship) study, we generate many linear substructure patterns like "NH-C-C-C-OH" from the data set of molecular structures. Matching between a pattern and a molecule leads to an item [pattern: y or n] depending on whether the pattern exists in the molecule. Application of the cascade model to this item data set gives us SAR rules. The resulting rules are examined by referring to the supporting molecular structures. Several rules have led to valuable working hypotheses, including the importance of steric hindrance to the coplanarity of NO2 to the activity level.
