skdim.id.FisherS.fit

FisherS.fit(X, y=None)[source]

A reference implementation of a fitting function.

Parameters:
X : {array-like}, shape (n_samples, n_features)

The training input samples.

y : dummy parameter to respect the sklearn API
Returns:

  • self (object) – Returns self.
  • self.dimension_ (float) – The estimated intrinsic dimension
  • self.n_alpha (1D np.array, float) – Effective dimension profile as a function of alpha
  • self.n_single (float) – A single estimate for the effective dimension
  • self.p_alpha (2D np.array, float) – Distributions as a function of alpha, matrix with columns corresponding to the alpha values, and with rows corresponding to objects.
  • self.separable_fraction (1D np.array, float) – Separable fraction of data points as a function of alpha
  • self.alphas (2D np.array, float) – Input alpha values