Index _ | A | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U _ _compute_metrics() (MLClassificationPerformance method) _construct_anon_data() (Algorithm method) _predict() (MLClassificationPerformance method) _repr_html_() (Dataset method) (ITableDF method) _set_X_y_test_from_test_df() (MLClassificationPerformance method) A activate() (Parallel method) Algorithm (class in k_anonymization.core) all_datasets (Dataset attribute) all_hierarchies_df (HierarchiesDict attribute) all_sample_datasets (SampleDataset attribute) anonymize() (Algorithm method) (Datafly method) (LocalRecodingAlgorithm method) (Perturbation method) AutoSortedTagsInput (class in k_anonymization.utils) C calculate() (CAVG static method) (Discernibility static method) calculate_best_effort() (CAVG static method) (Discernibility static method) calculate_for_generalization() (NCP static method) calculate_for_local_recoding_mean_mode() (NCP static method) calculate_for_local_recoding_summarization() (NCP static method) calculate_from_equivalence_classes() (CAVG static method) (Discernibility static method) CAVG (class in k_anonymization.evaluation.data_utility) ClassicMondrian (class in k_anonymization.algorithms.local_recoding) contains() (Hierarchy method) D Datafly (class in k_anonymization.algorithms.full_generalization) Dataset (class in k_anonymization.core) deactivate() (Parallel method) describe() (Dataset method) df (Dataset attribute) (SampleDataset attribute) Discernibility (class in k_anonymization.evaluation.data_utility) do_classic_mondrian() (ClassicMondrian method) do_laplacian_noise() (Perturbation method) do_local_recoding() (ClassicMondrian method) (KMember method) (LocalRecodingAlgorithm method) (OKA method) do_retention_replacement() (Perturbation method) DT (MLClassifierExample attribute) E evaluate() (MLClassificationPerformance method) F find_best_cluster() (KMember method) (OKA method) find_best_record() (KMember method) find_furthest_record_from_r() (KMember method) find_not_k_anonymous_qids() (in module k_anonymization.evaluation.anonymity) from_csv() (Hierarchy class method) from_json() (Hierarchy class method) G GENERALIZATION() (GroupAnonymizationBuiltIn static method) generalize_column() (in module k_anonymization.algorithms.utils) get_adjusting_records() (OKA method) get_equivalence_classes() (in module k_anonymization.evaluation.anonymity) get_height_of_node() (Hierarchy method) get_ITable_widget() (in module k_anonymization.utils.data_table) get_k_anonymity() (in module k_anonymization.evaluation.anonymity) get_leaves_under_node() (Hierarchy method) get_lowest_common_ancestor() (Hierarchy method) GroupAnonymization (in module k_anonymization.algorithms.local_recoding) GroupAnonymizationBuiltIn (class in k_anonymization.algorithms.local_recoding) H height (Hierarchy attribute) hierarchies (Dataset attribute) HierarchiesDict (class in k_anonymization.core) Hierarchy (class in k_anonymization.core) hierarchy_df (Hierarchy attribute) I info (Dataset attribute) init_clusters() (OKA method) is_categorical (Dataset attribute) is_k_anonymous() (in module k_anonymization.evaluation.anonymity) ITableDF (class in k_anonymization.core) K k_anonymization.algorithms module k_anonymization.algorithms.full_generalization module k_anonymization.algorithms.local_recoding module k_anonymization.algorithms.probabilistic module k_anonymization.algorithms.utils module k_anonymization.core module k_anonymization.evaluation module k_anonymization.evaluation.anonymity module k_anonymization.evaluation.data_utility module k_anonymization.evaluation.machine_learning module k_anonymization.utils module k_anonymization.utils.data_table module KMember (class in k_anonymization.algorithms.local_recoding) KNN (MLClassifierExample attribute) L leaves (Hierarchy attribute) LocalRecodingAlgorithm (class in k_anonymization.algorithms.local_recoding) LOG (MLClassifierExample attribute) M max_cores (Parallel attribute) MEAN_MODE() (GroupAnonymizationBuiltIn static method) MLClassificationPerformance (class in k_anonymization.evaluation.machine_learning) MLClassifierExample (class in k_anonymization.evaluation.machine_learning) module k_anonymization.algorithms k_anonymization.algorithms.full_generalization k_anonymization.algorithms.local_recoding k_anonymization.algorithms.probabilistic k_anonymization.algorithms.utils k_anonymization.core k_anonymization.evaluation k_anonymization.evaluation.anonymity k_anonymization.evaluation.data_utility k_anonymization.evaluation.machine_learning k_anonymization.utils k_anonymization.utils.data_table N name (Hierarchy attribute) NCP (class in k_anonymization.evaluation.data_utility) O OKA (class in k_anonymization.algorithms.local_recoding) org_data (Algorithm attribute) P Parallel (class in k_anonymization.core) path (Dataset attribute) perform() (Parallel method) Perturbation (class in k_anonymization.algorithms.probabilistic) pick_attribute() (Datafly method) props (Dataset attribute) Q qids (Dataset attribute) qids_categorial (Dataset attribute) qids_idx (Dataset attribute) qids_idx_categorial (Dataset attribute) qids_idx_numerical (Dataset attribute) qids_numerical (Dataset attribute) R reload_df() (Dataset method) (SampleDataset method) RF (MLClassifierExample attribute) S sample() (Dataset method) SampleDataset (class in k_anonymization.core) show() (in module k_anonymization.utils.data_table) show_whole_table() (ITableDF method) solve_b_given_k() (Perturbation method) solve_p_given_k() (Perturbation method) sort_qids_idx() (ClassicMondrian method) SUMMARIZATION() (GroupAnonymizationBuiltIn static method) SVM (MLClassifierExample attribute) T target (Dataset attribute) U update_df() (MLClassificationPerformance method)
