Warning

This version of the documentation corresponds to the master branch of cleanlab source code from GitHub. To see the documentation for the latest pip-installed version, click here.

internal

Warning

These internal utility methods are intended for internal use within the cleanlab package. They are not guaranteed to be stable between different versions.

• util
  • remove_noise_from_class()
  • clip_noise_rates()
  • clip_values()
  • value_counts()
  • value_counts_fill_missing_classes()
  • get_missing_classes()
  • round_preserving_sum()
  • round_preserving_row_totals()
  • estimate_pu_f1()
  • confusion_matrix()
  • print_square_matrix()
  • print_noise_matrix()
  • print_inverse_noise_matrix()
  • print_joint_matrix()
  • compress_int_array()
  • train_val_split()
  • subset_X_y()
  • subset_labels()
  • subset_data()
  • extract_indices_tf()
  • unshuffle_tensorflow_dataset()
  • is_torch_dataset()
  • is_tensorflow_dataset()
  • csr_vstack()
  • append_extra_datapoint()
  • get_num_classes()
  • num_unique_classes()
  • get_unique_classes()
  • format_labels()
  • smart_display_dataframe()
  • force_two_dimensions()
• latent_algebra
  • compute_ps_py_inv_noise_matrix()
  • compute_py_inv_noise_matrix()
  • compute_inv_noise_matrix()
  • compute_noise_matrix_from_inverse()
  • compute_py()
  • compute_pyx()
• label_quality_utils
  • get_normalized_entropy()
• multilabel_utils
  • stack_complement()
  • get_onehot_num_classes()
  • int2onehot()
  • onehot2int()
• multilabel_scorer
  • ClassLabelScorer
    • ClassLabelScorer.SELF_CONFIDENCE
    • ClassLabelScorer.NORMALIZED_MARGIN
    • ClassLabelScorer.CONFIDENCE_WEIGHTED_ENTROPY
    • ClassLabelScorer.__call__()
    • ClassLabelScorer.from_str()
    • ClassLabelScorer.__contains__()
    • ClassLabelScorer.__getitem__()
    • ClassLabelScorer.__iter__()
    • ClassLabelScorer.__len__()
  • exponential_moving_average()
  • softmin()
  • Aggregator
    • Aggregator.possible_methods
    • Aggregator.__call__()
  • MultilabelScorer
    • MultilabelScorer.__call__()
    • MultilabelScorer.aggregate()
    • MultilabelScorer.get_class_label_quality_scores()
  • get_label_quality_scores()
  • multilabel_py()
  • get_cross_validated_multilabel_pred_probs()
• neighbor
  • knn_graph
    • DEFAULT_K
    • features_to_knn()
    • construct_knn_graph_from_index()
    • create_knn_graph_and_index()
    • correct_knn_graph()
    • correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace()
    • correct_knn_distances_and_indices()
  • metric
    • HIGH_DIMENSION_CUTOFF
    • ROW_COUNT_CUTOFF
    • decide_euclidean_metric()
    • decide_default_metric()
  • search
    • construct_knn()
• outlier
  • transform_distances_to_scores()
  • correct_precision_errors()
• token_classification_utils
  • get_sentence()
  • filter_sentence()
  • process_token()
  • mapping()
  • merge_probs()
  • color_sentence()
• validation
  • assert_valid_inputs()
  • assert_valid_class_labels()
  • assert_nonempty_input()
  • assert_indexing_works()
  • labels_to_array()
  • labels_to_list_multilabel()