A data mining algorithm based on the rough sets theory and BP neural network

Weijin Jiang; Yusheng Xu; Yuhui Xu

doi:10.1117/12.651108

2 December 2005 A data mining algorithm based on the rough sets theory and BP neural network

Weijin Jiang, Yusheng Xu, Yuhui Xu

Proceedings Volume 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications; 604519 (2005) https://doi.org/10.1117/12.651108
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

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.

Citation Download Citation

Weijin Jiang, Yusheng Xu, and Yuhui Xu "A data mining algorithm based on the rough sets theory and BP neural network", Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604519 (2 December 2005); https://doi.org/10.1117/12.651108

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