Fuzzy Attribute Implications: Computing Non-redundant Bases Using Maximal Independent Sets
نویسندگان
چکیده
This note describes a method for computation of non-redundant bases of attribute implications from data tables with fuzzy attributes. Attribute implications are formulas describing particular dependencies of attributes in data. A non-redundant basis is a minimal set of attribute implications such that each attribute implication which is true in a given data (semantically) follows from the basis. Our bases are uniquely given by so-called systems of pseudo-intents. We reduce the problem of computing systems of pseudo-intents to the problem of computing maximal independent sets in certain graphs. We outline theoretical foundations, the algorithm, and present demonstrating examples.
منابع مشابه
Fuzzy Attribute Logic: Attribute Implications, Their Validity, Entailment, and Non-redundant Basis∗
We present results related to if-then rules and extraction of if-then rules from data tables with fuzzy attibutes. We provide basic definitions and results related to validity of if-then rules, semantic entailment, non-redundant bases, automatic generation of non-redundant bases, and relationships to concept lattices over data with fuzzy attributes.
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