MulticlassLDA documentation

[pnavaro]

The documentation of fit function for MulticlassLDA wasn't displayed. I think i fixed it. There is no example for LDA so i made a simple one but I am not sure you want it. I can add it to the PR it you are interested. This is the scikit-learn example though.

using MultivariateStats, RDatasets, Plots

iris = dataset("datasets", "iris")

X = Matrix(iris[1:2:end,1:4])'
X_labels = Vector(iris[1:2:end,5])

pca = fit(PCA, X; maxoutdim=2)
Ypca = predict(pca, X)

lda = fit(MulticlassLDA, X, X_labels; outdim=2)
Ylda = predict(lda, X)

p = plot(layout=(1,2), size=(900,300))

for s in ["setosa", "versicolor", "virginica"]

    points = Ypca[:,X_labels.==s]
    scatter!(p[1], points[1,:],points[2,:],marker=:circle,linewidth=0, 
             label=s, legend=:bottomleft)
    points = Ylda[:,X_labels.==s]
    scatter!(p[2], points[1,:],points[2,:],marker=:circle,linewidth=0, 
             label=s, legend=:bottomleft)

end
display(p)

[wildart]

And example for LDA would be a nice addition. If you decide to submit PR, please follow the structure of PCA docs.

[pnavaro]

Thanks for your useful comments. I append the example to the LDA page.

[wildart]

You may want to move example in the beginning on the page, just under the LDA description. So it will show up in TOC in the first place.

[pnavaro]

You may want to move example in the beginning on the page, just under the LDA description. So it will show up in TOC in the first place.

Yes it's consistent with the page on principal component analysis.