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- 博主最近在看临床预测模型,里面涉及到一些神经网络的相关知识,这里记录一下博主的简单理解。 基本概念 X:一个nx维的输入张量,可以是nx=0的标量,nx=1的向量,nx=2的矩阵,或更高维的张量 Y:一个ny维的输出张量,可以是nx=0的标量,nx=1的向量,nx=2的矩阵,或更高维的张量 f:一个特定结构的神经网络,如简单的BP神经网络
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- TMM:The Trimmed Mean of M value by edgeR VST:The variance stabilizing transformation by DESeq2 RLOG:The regularized-logarithm transformation by DESeq2 Counts矩阵来源于STAR匹配得到的结果:df <- read.csv('G
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