Validation catalogs, dataset containers, loaders, registry metadata, and dataset meta-feature helpers.

Package source: tabnetics.datasets

Package overview

Dataset registry, catalogs, loaders, and meta-features for validation-catalog and benchmark runs; when the HuggingFace bundle is configured, it acts as the authoritative operational mirror of the public upstream validation data sources.

Stable exports

  • CATALOG (constant) - Source. Module-level constant exported by the package surface.
  • DATASET_SETS (constant) - Source. Module-level constant exported by the package surface.
  • def extract_meta_features(X: np.ndarray, y: np.ndarray, *, expanded: bool = False, skip_distance_matrix: bool = False) -> Dict[str, float] (function) - Source. Extract dataset meta-features useful for tier assignment and analysis.
  • tabnetics.datasets.loaders - Source. Dataset loader exports.
  • tabnetics.datasets.meta_features - Source. Dataset meta-feature extraction helpers.
  • tabnetics.datasets.registry - Source. DatasetSpec registry (single source of truth for validation + benchmark datasets).
  • tabnetics.datasets.validation_catalog - Source. Validation catalog and dataset-set definitions.

Module details

tabnetics.datasets.__init__

Source file

Dataset registry, catalogs, loaders, and meta-features for validation-catalog and benchmark runs; when the HuggingFace bundle is configured, it acts as the authoritative operational mirror of the public upstream validation data sources.

No top-level public symbols are exported directly from this module.

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