A practical introduction to data structures and algorithm analysis
A practical introduction to data structures and algorithm analysis
Rough set methods and applications: new developments in knowledge discovery in information systems
Rough set methods and applications: new developments in knowledge discovery in information systems
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A reduction algorithm meeting users' requirements
Journal of Computer Science and Technology
Approximate Reducts and Association Rules - Correspondence and Complexity Results
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
A rough set paradigm for unifying rough set theory and fuzzy set theory
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
A view on rough set concept approximations
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Rough set approach to domain knowledge approximation
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
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As both rough sets theory and neural network in data mining have special advantages and exiting problems, this paper presented a combined algorithm based rough sets theory and BP neural network. This algorithm deducts data from data warehouse by using rough sets' deduct function, and then moves the deducted data to the BP neural network as training data. By data deduct, the expression of training will become clearer, and the scale of neural network can be simplified. At the same time, neural network can easy up rough set's sensitivity for noise data. This paper presents a cost function to express the relationship between the amount of training data and the precision of neural network, and to supply a standard for the change from rough set deduct to neural network training.