Momentum Backpropagation Optimization for Cancer Detection Based on DNA Microarray Data
作者： Untari Novia Wisesty , Febryanti Sthevanie , Rita Rismala
关键词:
摘要: Early detection of cancer can increase the success treatment in patients with cancer. In latest research, be detected through DNA Microarrays. Someone who suffers from will experience changes value certain gene expression. In previous studies, Genetic Algorithm as a feature selection method and Momentum Backpropagation algorithm classification provide fairly high performance, but still has low convergence rate because learning used is static. The makes training process need more time to converge. Therefore, this research an optimization done by adding adaptive scheme. proposed scheme proven reduce number epochs needed 390 76 compared algorithm. gain accuracy 90.51% for Colon Tumor data, 100% Leukemia, Lung Cancer, Ovarian Cancer data.
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sci-hub.st 参考文章(19)
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