Rough Set Theory: A True Landmark in Data Analysis

Theoretical Contributions to Rough Set Theory.- Rough Sets on Fuzzy Approximation Spaces and Intuitionistic Fuzzy Approximation Spaces.- Categorical Innovations for Rough Sets.- Granular Structures and Approximations in Rough Sets and Knowledge Spaces.- On Approximation of Classifications, Rough Equalities and Rough Equivalences.- Rough Set Data Mining Activities.- Rough Clustering with Partial Supervision.- A Generic Scheme for Generating Prediction Rules Using Rough Sets.- Rough Web Caching.- Software Defect Classification: A Comparative Study of Rough-Neuro-fuzzy Hybrid Approaches with Linear and Non-linear SVMs.- Rough Hybrid Models to Classification and Attribute Reduction.- Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem.- Nature Inspired Population-Based Heuristics for Rough Set Reduction.- Developing a Knowledge-Based System Using Rough Set Theory and Genetic Algorithms for Substation Fault Diagnosis.