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在高维微阵列数据中选择特征的修改强大的比例重叠得分

Muhammad Hamraz1, Tahir Abbas2, Fawad Ali1

  • 1Department of Statistics, Abdul Wali Khan University, Mardan, 23200, Pakistan.

Computers in biology and medicine
|April 15, 2025
PubMed
概括

修改后的强大比例重叠评分 (MRPOS) 从高维基基因表达数据中有效地选择歧视性基因. 这种新的特征选择方法解决了维度的诅咒,提高了生物研究中的分类准确性.

关键词:
错误分类是因为分类错误.基因表达 基因表达 基因表达重叠得分的得分重叠.随机的森林随机的森林鲁塞乌和克鲁统计数据支持矢量机器 (SVM) 是一个支持矢量机器.k-最近的邻居 (k-NN)

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