MultivariateDataAnalysis.jl
Multivariate data analysis using geometric algorithms made easy!
The package MultivariateDataAnalysis aims to provide an easy to use interface for a wide variety of multivariate statistical models like Principal Component Analysis, Linear Discriminant Analysis, Independent Component Analysis, VARIMAX and their variants, especially those formulated using geometric algorithms. It extends the StatsAPI.jl interface.
It is similar in scope to MultivariateStats.jl, although it MultivariateDataAnalysis aims to provide a wider variety of methods that require additional dependencies on optimization libraries.
Example usage:
using Manifolds, MultivariateDataAnalysis, RDatasets
data = Array(dataset("datasets", "iris")[!, Not(:Species)])
model = MDASubspaceModel(MaxVar(), Grassmann(size(data, 2), 2))
mf = fit(model, data)
predict(mf, [5.0, 3.0, 2.0, 1.0])