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Showing content from https://github.com/JuliaStats/MultivariateStats.jl/issues/109 below:

Unified API · Issue #109 · JuliaStats/MultivariateStats.jl · GitHub

Following #95, I looked at MV models/methods implemented in this package, trying to figure out what would be a type hierarchy and corresponding method interfaces for this package.

Here is a table of models and corresponding function names used by models.

Function \ Model CCA WHT ICA LDA FA PPCA PCA KPCA MDS fit x x x x x x x x x transform x x x x x x x x x predict x indim x x x x x x x x outdim x x x x x x x x x mean x x x x x x x ? var x x ? ? ? cov x ? cor x projection x x x x x x reconstruct x x x x loadings ? ? x x ? ? ? eigvals ? ? ? ? x eigvecs ? ? ? ? ? length size

I put ? where a possible implementation is missing or called differently.

So, I propose following type hierarchy

StatsBase.RegressionModel
- Methods: CCA, LDA
- Functions: fit, transfrom, indim, outdim, mean
- Subtypes:
  - AbstractDimensionalityReduction
  - Functions: projection, var, reconstruct, loadings
  - Subtypes:
    - LinearDimensionalityReduction
      - Methods: ICA, PCA
    - NonlinearDimensionalityReduction
      - Methods: KPCA, MDS
    - LatentVariableModel or LatentVariableDimensionalityReduction
      - Methods: FA, PPCA
      - Functions: cov
StatsBase.AbstractDataTransform
- Whitening
- Functions: fit, transfrom, indim, outdim, mean, size

@nalimilan @ararslan Thoughts?

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