公开(公告)号：US11837329B2

公开(公告)日：2023-12-05

申请号：US17798352

申请日：2022-02-22

申请人： NANTONG UNIVERSITY

发明人： Weiping Ding ,  Yu Geng ,  Jialu Ding ,  Hengrong Ju ,  Jiashuang Huang ,  Chun Cheng ,  Ying Sun ,  Yi Zhang ,  Ming Li ,  Tingzhen Qin ,  Xinjie Shen ,  Haipeng Wang

IPC分类号： G16B40/20 ,  G16H50/20

CPC分类号： G16B40/20 ,  G16H50/20

摘要： A method for classifying multi-granularity breast cancer genes based on a double self-adaptive neighborhood radius includes large-scale gene locus data are read and normalized, and a data analysis is performed on the large-scale gene loci. An optimum value K is selected by adopting a combination of contour coefficients and a PCA dimensionality reduction visualization, and a model of information granulation is adjusted. A heuristic reduction algorithm is used to implement a multi-granularity attribute reduction of a self-adaptive neighborhood radius based on a cluster center distance and a multi-granularity attribute reduction of a neighborhood radius based on an attribute inclusion degree, and big data for breast cancer genes are classified and predicted by adopting a machine learning classification algorithm based on a SVM support vector machine.