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Summary. „Rough sets and Data mining” Vietnam national university in H anoi , College of technology , Feb.2006. Main topics:. Definition, principles and functionalities of data mining systems Rough sets methodology to concept approximation and data mining
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Summary „Rough sets and Data mining” Vietnam national university inHanoi, College of technology, Feb.2006
Main topics: • Definition, principles and functionalities of data mining systems • Rough sets methodology to concept approximation and data mining • Boolean reasoning approach to problem solving • Data preprocessing and data cleaning methods • Association rules • Classification methods
Boolean reasoning methodology • Monotone Boolean function • Implicant, prime implicant • Searching for minimal prime implicants of a monotone Boolean function
Data preprocessing and data cleaning • Discretization methods • Data reduction methods • Missing values • Outlier elimination • Rough set methods for discretization and attribute reduction
Association rules • Definition, possible applications • Apriori search for frequent patterns and association rules • Modifications of apriori algorithms: hash tree, Apriori-Tid, Apriori-Hybrid • FP-tree method • Relationship between association rule and rough set methods
Classification methods • Instance-based classification techniques • Bayesian classifiers • Decision tree methods • Decision rules methods • Classifier evaluation techniques
Discernibility measure • Applications of discernibility measure in • Feature selection • Discretization • Symbolic value grouping • Decision tree construction