Attribute Reduction Based on Continuous Attribute Domain

Yi Zhang

doi:10.4028/www.scientific.net/AMR.1044-1045.1084

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1044-1045Attribute Reduction Based on Continuous Attribute...

Attribute Reduction Based on Continuous Attribute Domain

Abstract:

Discrete data attributes reduction, there are many mature methods, but for continuous data attributes reduction, general algorithm is not very good, in real life, the continuous data feature extraction and discrete data is also important, based on the number of new brain waves as analysis object, and through the continuous eeg feature extraction comparison, verify the feasibility of the proposed method.

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Periodical:

Advanced Materials Research (Volumes 1044-1045)

Pages:

1084-1087

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1084

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Online since:

October 2014

Authors:

Yi Zhang

Keywords:

Attribute Reduction, Continuous Attribute Domain, Data Mining

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References

[1] Zhang Yanping, Mr Luo, yao yu. Quotient space theory and method and granular computing - structured problem solving [J]. (2010).

Google Scholar

[2] Qian Yuhua. The granulating mechanism of complex data and data modeling [D]. Taiyuan, shanxi university, (2011).

Google Scholar

[3] Zhendong Mu, Dan Xiao, Jianfeng Hu. （2009）Classification of motor imagery EEG signals based on time–frequency analysis. International Journal of Digital Content Technology and its Applications Volume 3, 2009：116-119.

DOI: 10.4156/jdcta.vol3.issue4.13

Google Scholar

[4] Zhengdong Mu, Jianfeng Hu. （2009）Research of EEG Identification Computing Based on AR Model. 2009 international conference on future biomedical information engineering, 2009: 366-368.

DOI: 10.1109/fbie.2009.5405847

Google Scholar

[5] Zhendong Mu, Derong Jiang, Jinghai Yin, EEG identification computing based on photo stimulation, International Journal of Digital Content Technology and its Applications, Vol. 6, No. 13, 2011, pp.549-556.

DOI: 10.4156/jdcta.vol6.issue13.58

Google Scholar

[6] Zhengdong Mu, Jinghai Yin, Jianfeng Hu. （2010）Research on motor imagery based on mobile platform，2010 The 2nd Conference on Environmental Science and Information Application Technology，1364-1369.

Google Scholar

[6] Zhendong Mu, Derong Jiang, Jinghai Yin, EEG identification computing based on photo stimulation, International Journal of Digital Content Technology and its Applications, Vol. 6, No. 13, 2011, pp.549-556.

DOI: 10.4156/jdcta.vol6.issue13.58

Google Scholar

[7] Zhengdong Mu, Jinghai Yin, Jianfeng Hu. （2010）Research on motor imagery based on mobile platform，2010 The 2nd Conference on Environmental Science and Information Application Technology，1364-1369.

Google Scholar