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Support Vector Regression for Unsupervised Machine Learning

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Is this what `readlibsvmfile` is for? ```julia julia> x, y = SVR.readlibsvmfile("rcv1subset_topics_train_1.svm") ERROR: BoundsError: attempt to access 1-element Vector{SubString{String}} at index [2] Stacktrace: [1] getindex(A::Vector{SubString{String}}, i1::Int64) @ Base ./array.jl:861 [2]...

When I try to build SVR I am facing the following error > ┌ Error: Error building `SVR`: > │ ERROR: LoadError: IOError: could not spawn `make clean`: no such...

Hi and thanks for this package! Have you considered porting it's features to the interface [MLJ](https://github.com/alan-turing-institute/MLJ.jl).jl? Here is the equivalent code: https://github.com/alan-turing-institute/MLJModels.jl/blob/master/src/LIBSVM.jl

in [cjlin1/libsvm](https://github.com/cjlin1/libsvm), svmtrain has an extra option `-v n: n-fold cross validation mode` is it possible to add this option to SVR?