Abstract
In order to improve the accuracy of the classification of the big data of disease gene detection, an algorithm for the classification of the big data of disease gene detection based on the complex network technology was proposed. On the basis of complex network technology, a distance-based membership function is first established. Considering the distance between the sample and the class center, the membership function of sample compactness is designed to complete the establishment of membership function of complex network. Combined with the design of the classification algorithm flow of the big data of disease gene detection, the design of the data classification algorithm was completed, and the classification of the big data of disease gene detection was realized. The experimental results show that the proposed algorithm is more accurate than the other two classification algorithms in the big data sets of different disease genes.
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Gao, Yy., Xiang, J., Tang, Yn., He, M., Li, W. (2021). Research on Big Data Classification Algorithm of Disease Gene Detection Based on Complex Network Technology. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-030-67871-5_28
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DOI: https://doi.org/10.1007/978-3-030-67871-5_28
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