A Model of User-Oriented Reduct Construction for Machine Learning

DOI10.1007/978-3-540-85064-9_15zbMath1170.68573OpenAlexW2116587871MaRDI QIDQ3600310

Suqing Han, Jue Wang, Yan Zhao, Y. Y. Yao

Publication date: 10 February 2009

Published in: Transactions on Rough Sets VIII (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-85064-9_15

zbMATH Keywords

attribute reductionuser preferenceconditional user preference

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Analysis of alternative objective functions for attribute reduction in complete decision tables ⋮ A rule induction algorithm in incomplete decision table based on attribute order

Uses Software

• CP-nets
• LERS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Selection of relevant features and examples in machine learning
• Wrappers for feature subset selection
• Analysis on attribute reduction strategies of rough set
• Rough approximation of a preference relation by dominance relations
• A reduction algorithm meeting users' requirements.
• Knowledge reduction based on the equivalence relations defined on attribute set and its power set
• A Model of Machine Learning Based on User Preference of Attributes
• Rough sets
• Rough set methods in feature selection and recognition
• Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
• Approximate Boolean Reasoning: Foundations and Applications in Data Mining
• On Reduct Construction Algorithms
• Knowledge Reduction in Incomplete Information Systems Based on Dempster-Shafer Theory of Evidence
• Reducts within the variable precision rough sets model: A further investigation
• Reduction algorithms based on discernibility matrix: The ordered attributes method

This page was built for publication: A Model of User-Oriented Reduct Construction for Machine Learning