mining functional dependencies from data
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Mining Functional Dependencies from Data. Hong Yao and Howard J. Hamilton Presented By Stephen Lynn. Rule Mining. Algorithmic process that takes data as input and yields rules such as: Association Rules Implications Functional dependencies. Overview. Goals/Objectives - PowerPoint PPT PresentationTRANSCRIPT
Ontology Learning
Mining Functional Dependencies from Data
Hong Yao and Howard J. Hamilton
Presented By Stephen Lynn
Ontology Learning
Rule Mining
Algorithmic process that takes data as input and yields rules such as:
Association Rules ImplicationsFunctional dependencies
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Overview Goals/Objectives Implication/Functional Dependencies Base Algorithm 4 Pruning Rules Evaluation Analysis
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Goals and Objectives
Design an efficient rule discovery algorithm for mining functional dependencies from a dataset.
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Implication Describes relationship between one specific
combination of attribute-value pairs.Binary DataPropositional Logic
{milk, eggs} → {bread}
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Functional Dependency Describe relationship between all possible
combinations of attribute-value pairs.Disjoint attributesTrue regardless of how many possible attribute valuesantecedent → consequent
postcode → areacode
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Search Space
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Armstrong’s Axioms
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Equivalent Attributes
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Nontrivial Closure
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Base Algorithm Generate all possible antecedents then test with
possible consequents (1 level at a time)
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Pruning Rules
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FD_Mine
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Experimental Summary 15 Datasets from UCI Machine Learning Repository
(2005)
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Results
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Results
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Runtime
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Analysis Strengths
Nicely drawn proofs Weaknesses
Missing good exampleNice to show results with/without pruning
Future WorkFind multivalued dependenciesFind conditional dependenciesData cleaning