期刊名称:IOP Conference Series: Earth and Environmental Science
印刷版ISSN:1755-1307
电子版ISSN:1755-1315
出版年度:2018
卷号:153
期号:3
页码:032009
DOI:10.1088/1755-1315/153/3/032009
语种:English
出版社:IOP Publishing
摘要:Based on mirna expression spectrum data set, a new data mining algorithm - tSVM - KNN (t statistic with support vector machine - k nearest neighbor) is proposed. the idea of the algorithm is: firstly, the feature selection of the data set is carried out by the unified measurement method; Secondly, SVM - KNN algorithm, which combines support vector machine (SVM) and k - nearest neighbor (k - nearest neighbor) is used as classifier. Simulation results show that SVM - KNN algorithm has better classification ability than SVM and KNN alone. Tsvm - KNN algorithm only needs 5 mirnas to obtain 96.08 % classification accuracy in terms of the number of mirna " tags" and recognition accuracy. compared with similar algorithms, tsvm - KNN algorithm has obvious advantages.