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Generate synthetic data for manifold learning

manifold_synthetic_data.Rd

A unified wrapper function for generating various types of synthetic data to test manifold learning techniques and demonstrate differences.

Usage

manifold_synthetic_data(
  type = c("swiss_role", "biased_swiss_role", "clusters", "trajectory", "hierarchical"),
  n_samples,
  dim = 32L,
  seed = 42L,
  parameters = NULL
)

Arguments

type

Character. Type of synthetic data to generate. One of:

  • "swiss_role" - Swiss roll manifold

  • "biased_swiss_role" - Biased swiss role manifold

  • "clusters" - Clustered data

  • "trajectory" - Trajectory-like data with branching

  • "hierarchical" - Two-level hierarchical cluster structure

n_samples

Integer. Number of data points to generate.

dim

Integer. Dimensionality of the ambient space. Used for all types except "swiss_role". Defaults to 32L.

seed

Integer. Seed for reproducibility. Defaults to 42L.

parameters

A named list of type-specific parameters, constructed via params_swiss_role(), params_swiss_role_biased() params_clusters(), params_trajectory(), or params_hierarchical(). If NULL, defaults for the chosen type are used. A plain list is accepted but must contain all required fields for the given type.

Value

A list with the following elements:

  • data - Numeric matrix of shape n_samples x dim

  • membership - Integer vector of cluster/branch assignments (NULL for "swiss_role")