Actually, I'm trying to implement Multivaritate Gaussian distribution on a dataset from a data center. The data table NETWORK_DATA_TRAINING
is stored in the Oracle database . But, when I tried to replicated the Matrix with columnwise means, it threw an error:
library(ORE)
library(pracma)
if (!ore.is.connected())
ore.connect("NETWORK_TBL01", "orcl","192.168.50.19", "test",port=1521, all=TRUE)
X <- NETWORK_DATA_TRAINING[,]
Mu <- colMeans(X) # class(X) : "ore.frame" , dim(X): 1000 11
Mu <- as.matrix(Mu) #class(Mu) : "ore.tblmatrix", dim(Mu):1 11
k <- ncol(Mu)
mu <- matrix(Mu,ncol(X),nrow(X))
error: no method for coercing this S4 class to a vector
X <- bsxfun("-", X, mu)
print(X)
For more, here goes the link .
实际上,在强制转换为矩阵之前,我不得不使用转换表。
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