KernelPCA was added to
MultivariateStats pretty recently and the developers haven’t tagged a new release since it was added. If you installed
MultivariateStats by running
then you’ll be using the latest release of the package, which does not include KernelPCA. When you go to https://github.com/JuliaStats/MultivariateStats.jl and click on the documentation link at the bottom of the README it brings you to the documentation as it exists on the master branch of the repository. You can run
Pkg.checkout("MultivariateStats") to try out the latest features. If you want to go back to the release version just do
Pkg.free("MultivariateStats"). Check out the package manager documentation for more information. The following worked for me:
INFO: Checking out MultivariateStats master...
INFO: Pulling MultivariateStats latest master...
INFO: No packages to install, update or remove
julia> Xtr = rand(100,10);
INFO: Recompiling stale cache file /home/patrick/.julia/lib/v0.6/MultivariateStats.ji for module MultivariateStats.
julia> M = fit(KernelPCA, Xtr; maxoutdim=100, inverse=true);
I don’t know about your second question unfortunately. To help out someone who might be able to answer it, are you using Plots.jl? In your example is
setosa a DataFrame? Can you make a scatter plot if you just pass three plain vectors to