Model flowchart

The following flowchart can be used as a guide to select the right estimator.

        graph TD;
  A(How many feature space ?)
  O(Data size ?)
  M(Data size ?)
  OR(Hyperparameters ?)
  OK(Hyperparameters ?)
  MR(Hyperparameters ?)
  MK(Hyperparameters ?)

  A-- one-->O;
  A--multiple-->M;
  O--more samples-->OR;
  O--more features-->OK;
  M--more samples-->MR;
  M--more features-->MK;

  OK--known-->OKH[KernelRidge];
  OK--unknown-->OKCV[KernelRidgeCV];
  OR--known-->ORH[Ridge];
  OR--unknown-->ORCV[RidgeCV];
  MK--known-->MKH[WeightedKernelRidge];
  MK--unknown-->MKCV[MultipleKernelRidgeCV];

  MR--unknown-->MRCV[BandedRidgeCV];
  MR--known-->MKH;

  classDef fork fill:#FFDC97
  class A,O,M,OR,OK,MR,MK fork;

  classDef leaf fill:#ABBBE1
  class ORH,OKH,MRH,MKH leaf;
  class ORCV,OKCV,MRCV,MKCV leaf;

  click ORH "https://gallantlab.github.io/himalaya/_generated/himalaya.ridge.Ridge.html"
  click ORCV "https://gallantlab.github.io/himalaya/_generated/himalaya.ridge.RidgeCV.html"
  click MRCV "https://gallantlab.github.io/himalaya/_generated/himalaya.ridge.BandedRidgeCV.html"
  click OKH "https://gallantlab.github.io/himalaya/_generated/himalaya.kernel_ridge.KernelRidge.html"
  click OKCV "https://gallantlab.github.io/himalaya/_generated/himalaya.kernel_ridge.KernelRidgeCV.html"
  click MKH "https://gallantlab.github.io/himalaya/_generated/himalaya.kernel_ridge.WeightedKernelRidge.html"
  click MKCV "https://gallantlab.github.io/himalaya/_generated/himalaya.kernel_ridge.MultipleKernelRidgeCV.html"