Julia, Stats, Unsupervised Learning, Math, Julialang.
the original data. Plots using Plots h = plot(q[1,:], q[2,:], seriestype=:scatter, label=label="") plot!(xlabel="PC1", ylabel="PC2", framestyle=:box) title!("Principal Components") T = principalvars(M) ./ tvar(M) * 100 ‘principalvars’ are variances of principal components, ‘tvar(M)’ are the total