R语言中写出基于iris数据集，从协方差矩阵，即特征值分解出发的主成分求解法代码

这个问题可以回答。以下是基于iris数据集，从协方差矩阵，即特征值分解出发的主成分求解法的R语言代码。

# load the iris dataset
data(iris)

# calculate the covariance matrix
cov_mat <- cov(iris[, 1:4])

# get the eigenvalues and eigenvectors of the covariance matrix
eig <- eigen(cov_mat)

# sort the eigenvalues in decreasing order
eig_val <- eig$values
eig_val_idx <- order(eig_val, decreasing = TRUE)
eig_val <- eig_val[eig_val_idx]
eig_vec <- eig$vectors[, eig_val_idx]

# calculate the principal components
pc <- as.matrix(iris[, 1:4]) %*% eig_vec

# plot the first two principal components
plot(pc[,1], pc[,2], col = iris$Species, pch = 19, xlab = "PC1", ylab = "PC2")
legend("topleft", legend = levels(iris$Species), pch = 19, col = 1:length(levels(iris$Species)))