Question

我有5个维度的空间质心，以centroid<-c(-0.0160560385542169, -0.0125691807228916, -0.000605079518072289, -0.00174781445783133, -0.0199511518072289)给出。我还有一个包含5个样本的矩阵，其中PCA1:PCA5表示这些样本的5个维度点。如何从质心计算每个样本的欧氏距离？如果是从一个点到另一个点的距离，我可以简单地完成dist(mymat[,-1])，但我不确定如何从质心获得距离。有人可以建议吗？

mymat<- structure(c("10687:G41F", "10687:SKDP-225.3", "10687:2671", "10687:LPH-001-16_SCC", 
"10687:MC1R-694CB-T", "-0.0039950", "-0.0203415", "-0.0200395", 
"-0.0147320", "-0.0196970", "-0.0140180", "-0.0181240", "-0.0165090", 
"-0.0148700", "-0.0170765", "-0.0136615", "-0.0010915", "-0.0014500", 
" 0.0020240", "-0.0021095", "-0.0002395", "-0.0019710", "-0.0017595", 
" 0.0036180", "-0.0036255", "-0.0184015", "-0.0197400", "-0.0238185", 
"-0.0282375", "-0.0323130"), .Dim = 5:6, .Dimnames = list(c("1", 
"2", "3", "4", "5"), c("samples", "PCA1", "PCA2", "PCA3", 
"PCA4", "PCA5")))

Answer 1

dist应该推广到你想要的多个维度......

centroid <- c(-0.0160560385542169, -0.0125691807228916, -0.000605079518072289, 
 -0.00174781445783133, -0.0199511518072289)
rbind(c("centroid", centroid), mymat) -> k
dist(k, "euclidean") -> dd
as.matrix(dd) -> dd
k[,1] -> rownames(dd) 
as.data.frame(dd)
dd[2:6,1] -> dist_to_centroid
View(as.data.frame(dist_to_centroid))

如何计算多维空间中距质心的点的距离

1 个答案: