differentiate MDS and PCA in Julia

Question

I'm using both MDS and PCA in the package MultivariateStats.jl. My code is

 M = fit(PCA, matrix; maxoutdim=2)
Yte = predict(M, matrix)
M1 = fit(MDS, matrix; maxoutdim=2, distances=false)
Yte1 = predict(M1)

Soon I found that Yte and Yte1 are always the same since MDS uses Euclidean norm, so MDS is always equivalent to PCA in this case. Then I tried another method.

mds = fit(MDS, matrix; distances=true, metric=isotonic)

But I got the error that

MethodError: no method matching fit(::Type{MDS}, ::Adjoint{Float64, Matrix{Float64}}; distances=true, metric=MultivariateStats.isotonic) Closest candidates are: fit(::Type{MDS}, ::AbstractMatrix{T}; maxoutdim, distances) where T<:Real at ~/.julia/packages/MultivariateStats/cFZlL/src/cmds.jl:232 got unsupported keyword argument "metric"

I found the example code above in https://juliastats.org/MultivariateStats.jl/dev/mds/#MultivariateStats.MetricMDS

Is there anyway to fix it?

Please [report it here](https://github.com/JuliaStats/MultivariateStats.jl/issues/new/choose). Open an issue with a title like `MethodError: no method matching fit(::Type{MDS}, ::Adjoint{Float64, Matrix{Float64}}` and paste your entire post there. Thanks. — Shayan, Nov 15 '22 at 11:28

score 0 · Answer 1 · answered Nov 15 '22 at 01:25

0

I think the documentation is wrong, try MetricMDS instead of MDS.

answered Nov 15 '22 at 01:25

August

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UndefVarError: MetricMDS not defined – Joe Nov 15 '22 at 02:34
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Are you using v0.10.0 ? – August Nov 15 '22 at 02:52
I'm using v"1.8.1" – Joe Nov 15 '22 at 03:01
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I mean version of MultivariateStats. Try updating: `] update MultivariateStats` – August Nov 15 '22 at 18:49
The same error after the update. – Joe Nov 15 '22 at 19:10

differentiate MDS and PCA in Julia

1 Answers1