Fuzzy MLP based expert system for medical diagnosis
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Soft computing in case based reasoning
Soft computing in case based reasoning
A connectionist model for selection of cases
Information Sciences: an International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Self-Organizing Maps
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
Rough-Fuzzy C-Medoids Algorithm and Selection of Bio-Basis for Amino Acid Sequence Analysis
IEEE Transactions on Knowledge and Data Engineering
Recent Literature Collected by Didier DUBOIS, Henri PRADE and Salvatore SESSA
Fuzzy Sets and Systems
Using approximate reduct and LVQ in case generation for CBR classifiers
Transactions on rough sets VII
International Journal of Hybrid Intelligent Systems
Fuzzy rough granular self organizing map
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Review: Hybrid expert systems: A survey of current approaches and applications
Expert Systems with Applications: An International Journal
Divisible rough sets based on self-organizing maps
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Rough learning vector quantization case generation for CBR classifiers
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
A game-theoretic approach to competitive learning in self-organizing maps
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Fuzzy rough granular self-organizing map and fuzzy rough entropy
Theoretical Computer Science
Fundamenta Informaticae - Cognitive Informatics and Computational Intelligence: Theory and Applications
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A rough self-organizing map (RSOM) with fuzzy discretization of feature space is described here. Discernibility reducts obtained using rough set theory are used to extract domain knowledge in an unsupervised framework. Reducts are then used to determine the initial weights of the network, which are further refined using competitive learning. Superiority of this network in terms of quality of clusters, learning time and representation of data is demonstrated quantitatively through experiments over the conventional SOM.