Variable precision rough set model
Journal of Computer and System Sciences
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Information Sciences: an International Journal
Handling concept drifts in incremental learning with support vector machines
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Incremental Learning with Support Vector Machines
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
Information Sciences—Informatics and Computer Science: An International Journal
Rough set based incremental clustering of interval data
Pattern Recognition Letters
Information Sciences: an International Journal
Business Aviation Decision-Making Using Rough Sets
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Financial time-series analysis with rough sets
Applied Soft Computing
Rule induction based on an incremental rough set
Expert Systems with Applications: An International Journal
The parameterization reduction of soft sets and its applications
Computers & Mathematics with Applications
An Incremental Updating Algorithm of Attribute Reduction Set in Decision Tables
FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
A Dominance-based Rough Set Approach to customer behavior in the airline market
Information Sciences: an International Journal
The incremental method for fast computing the rough fuzzy approximations
Data & Knowledge Engineering
A rough set approach to multiple dataset analysis
Applied Soft Computing
Autonomous rule induction from data with tolerances in customer relationship management
Expert Systems with Applications: An International Journal
A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice
Applied Soft Computing
Several approaches to attribute reduction in variable precision rough set model
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Incremental learning and evaluation of structures of rough decision tables
Transactions on Rough Sets IV
Fundamenta Informaticae
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The rough set (RS) theory can be seen as a new mathematical approach to vagueness and is capable of discovering important facts hidden in that data. However, traditional rough set approach ignores that the desired reducts are not necessarily unique since several reducts could include the same value of the strength index. In addition, the current RS algorithms have the ability to generate a set of classification rules efficiently, but they cannot generate rules incrementally when new objects are given. Numerous studies of incremental approaches are not capable to deal with the problems of large database. Therefore, an incremental rule-extraction algorithm is proposed to solve these issues in this study. Using this algorithm, when a new object is added up to an information system, it is unnecessary to re-compute rule sets from the very beginning, which can quickly generate the complete but not repetitive rules. In the case study, the results show that the incremental issues of new data add-in are resolved and a huge computation time is saved.