skdim.id.lPCA.fit_pw

lPCA.fit_pw(X, precomputed_knn=None, smooth=False, n_neighbors=100, n_jobs=1)

Creates an array of pointwise ID estimates (self.dimension_pw_) by fitting the estimator in kNN of each point.

Parameters:

X : np.array (n_samples x n_neighbors)

Dataset to fit

precomputed_knn : np.array (n_samples x n_dims)

An array of precomputed (sorted) nearest neighbor indices

n_neighbors

Number of nearest neighbors to use (ignored when using precomputed_knn)

n_jobs : int

Number of processes

smooth : bool, default = False

Additionally computes a smoothed version of pointwise estimates by

taking the ID of a point as the average ID of each point in its neighborhood (self.dimension_pw_)

smooth_

Returns:

self (object) – Returns self