pysubgroup

• pysubgroup package
  • Submodules
  • pysubgroup.algorithms module
    • Apriori
      • Apriori.execute()
      • Apriori.get_next_level()
      • Apriori.get_next_level_candidates()
      • Apriori.get_next_level_candidates_vectorized()
      • Apriori.get_next_level_numba()
    • BeamSearch
      • BeamSearch.execute()
    • BestFirstSearch
      • BestFirstSearch.execute()
    • DFS
      • DFS.execute()
      • DFS.search_internal()
    • DFSNumeric
      • DFSNumeric.execute()
      • DFSNumeric.search_internal()
      • DFSNumeric.tpl
    • GeneralisingBFS
      • GeneralisingBFS.execute()
    • SimpleDFS
      • SimpleDFS.execute()
      • SimpleDFS.search_internal()
    • SimpleSearch
      • SimpleSearch.execute()
    • SubgroupDiscoveryTask
    • constraints_satisfied()
  • pysubgroup.binary_target module
    • BinaryTarget
      • BinaryTarget.calculate_statistics()
      • BinaryTarget.covers()
      • BinaryTarget.get_attributes()
      • BinaryTarget.get_base_statistics()
      • BinaryTarget.statistic_types
    • ChiSquaredQF
      • ChiSquaredQF.chi_squared_qf()
      • ChiSquaredQF.chi_squared_qf_weighted()
      • ChiSquaredQF.evaluate()
    • GeneralizationAware_StandardQF
      • GeneralizationAware_StandardQF.difference_based_agg_function()
      • GeneralizationAware_StandardQF.difference_based_optimistic_estimate()
      • GeneralizationAware_StandardQF.difference_based_read_p()
      • GeneralizationAware_StandardQF.evaluate()
      • GeneralizationAware_StandardQF.ga_sQF_agg_tuple
      • GeneralizationAware_StandardQF.max_based_aggregate_statistics()
      • GeneralizationAware_StandardQF.max_based_optimistic_estimate()
      • GeneralizationAware_StandardQF.max_based_read_p()
    • LiftQF
    • SimpleBinomialQF
    • SimplePositivesQF
      • SimplePositivesQF.calculate_constant_statistics()
      • SimplePositivesQF.calculate_statistics()
      • SimplePositivesQF.gp_get_null_vector()
      • SimplePositivesQF.gp_get_params()
      • SimplePositivesQF.gp_get_stats()
      • SimplePositivesQF.gp_merge()
      • SimplePositivesQF.gp_requires_cover_arr
      • SimplePositivesQF.gp_size_sg()
      • SimplePositivesQF.gp_to_str()
      • SimplePositivesQF.tpl
    • StandardQF
      • StandardQF.evaluate()
      • StandardQF.optimistic_estimate()
      • StandardQF.optimistic_generalisation()
      • StandardQF.standard_qf()
    • WRAccQF
  • pysubgroup.constraints module
    • ContainsValueConstraint
      • ContainsValueConstraint.attribute_name
      • ContainsValueConstraint.value
      • ContainsValueConstraint.is_monotone
      • ContainsValueConstraint.is_satisfied()
    • MinSupportConstraint
      • MinSupportConstraint.min_support
      • MinSupportConstraint.gp_is_satisfied()
      • MinSupportConstraint.gp_prepare()
      • MinSupportConstraint.is_monotone
      • MinSupportConstraint.is_satisfied()
    • MinUniqueValuesConstraint
      • MinUniqueValuesConstraint.attribute_name
      • MinUniqueValuesConstraint.min_unique_values
      • MinUniqueValuesConstraint.is_monotone
      • MinUniqueValuesConstraint.is_satisfied()
  • pysubgroup.datasets module
    • get_credit_data()
    • get_titanic_data()
  • pysubgroup.fi_target module
    • AreaQF
      • AreaQF.evaluate()
    • CountQF
      • CountQF.evaluate()
      • CountQF.optimistic_estimate()
    • FITarget
      • FITarget.calculate_statistics()
      • FITarget.get_attributes()
      • FITarget.get_base_statistics()
      • FITarget.statistic_types
    • SimpleCountQF
      • SimpleCountQF.calculate_constant_statistics()
      • SimpleCountQF.calculate_statistics()
      • SimpleCountQF.gp_get_null_vector()
      • SimpleCountQF.gp_get_params()
      • SimpleCountQF.gp_get_stats()
      • SimpleCountQF.gp_merge()
      • SimpleCountQF.gp_requires_cover_arr
      • SimpleCountQF.gp_size_sg()
      • SimpleCountQF.gp_to_str()
      • SimpleCountQF.tpl
  • pysubgroup.gp_growth module
    • GpGrowth
      • GpGrowth.GP_node
      • GpGrowth.minSupp
      • GpGrowth.tqdm
      • GpGrowth.depth
      • GpGrowth.mode
      • GpGrowth.constraints_monotone
      • GpGrowth.results
      • GpGrowth.task
      • GpGrowth.add_if_required()
      • GpGrowth.calculate_quality_function_for_patterns()
      • GpGrowth.check_constraints()
      • GpGrowth.check_tree_is_ordered()
      • GpGrowth.convert_results_to_subgroups()
      • GpGrowth.create_copy_of_path()
      • GpGrowth.create_copy_of_tree_top_down()
      • GpGrowth.create_initial_tree()
      • GpGrowth.create_new_tree_from_nodes()
      • GpGrowth.execute()
      • GpGrowth.get_nodes_upwards()
      • GpGrowth.get_stats_for_class()
      • GpGrowth.get_top_down_tree_for_class()
      • GpGrowth.merge_trees_top_down()
      • GpGrowth.nodes_to_cls_nodes()
      • GpGrowth.normal_insert()
      • GpGrowth.prepare_selectors()
      • GpGrowth.recurse()
      • GpGrowth.recurse_top_down()
      • GpGrowth.remove_selectors_with_low_optimistic_estimate()
      • GpGrowth.setup()
      • GpGrowth.setup_constraints()
      • GpGrowth.setup_from_quality_function()
      • GpGrowth.to_file()
    • identity()
  • pysubgroup.measures module
    • AbstractInterestingnessMeasure
      • AbstractInterestingnessMeasure.ensure_statistics()
    • BoundedInterestingnessMeasure
    • CombinedInterestingnessMeasure
      • CombinedInterestingnessMeasure.calculate_constant_statistics()
      • CombinedInterestingnessMeasure.calculate_statistics()
      • CombinedInterestingnessMeasure.evaluate()
      • CombinedInterestingnessMeasure.evaluate_from_statistics()
      • CombinedInterestingnessMeasure.optimistic_estimate()
    • CountCallsInterestingMeasure
      • CountCallsInterestingMeasure.calculate_statistics()
    • GeneralizationAwareQF
      • GeneralizationAwareQF.calculate_constant_statistics()
      • GeneralizationAwareQF.calculate_statistics()
      • GeneralizationAwareQF.evaluate()
      • GeneralizationAwareQF.ga_tuple
      • GeneralizationAwareQF.get_qual_and_previous_qual()
    • GeneralizationAwareQF_stats
      • GeneralizationAwareQF_stats.calculate_constant_statistics()
      • GeneralizationAwareQF_stats.calculate_statistics()
      • GeneralizationAwareQF_stats.evaluate()
      • GeneralizationAwareQF_stats.ga_tuple
      • GeneralizationAwareQF_stats.get_stats_and_previous_stats()
    • maximum_statistic_filter()
    • minimum_quality_filter()
    • minimum_statistic_filter()
    • overlap_filter()
    • overlaps_list()
    • unique_attributes()
  • pysubgroup.model_predictions_target module
    • ARLQF
    • BaseSoftClassifierPerformanceQF
      • BaseSoftClassifierPerformanceQF.calculate_constant_statistics()
      • BaseSoftClassifierPerformanceQF.calculate_statistics()
      • BaseSoftClassifierPerformanceQF.evaluate()
      • BaseSoftClassifierPerformanceQF.optimistic_estimate()
    • PRAUCQF
    • ROCAUCQF
    • SoftClassifierTarget
      • SoftClassifierTarget.calculate_statistics()
      • SoftClassifierTarget.get_target_columns()
      • SoftClassifierTarget.statistic_types
    • average_ranking_loss()
    • pr_auc_score()
  • pysubgroup.model_target module
    • EMM_Likelihood
      • EMM_Likelihood.calculate_constant_statistics()
      • EMM_Likelihood.calculate_statistics()
      • EMM_Likelihood.evaluate()
      • EMM_Likelihood.get_tuple()
      • EMM_Likelihood.gp_get_params()
      • EMM_Likelihood.gp_requires_cover_arr
      • EMM_Likelihood.tpl
    • PolyRegression_ModelClass
      • PolyRegression_ModelClass.calculate_constant_statistics()
      • PolyRegression_ModelClass.fit()
      • PolyRegression_ModelClass.gp_get_null_vector()
      • PolyRegression_ModelClass.gp_get_params()
      • PolyRegression_ModelClass.gp_get_stats()
      • PolyRegression_ModelClass.gp_merge()
      • PolyRegression_ModelClass.gp_requires_cover_arr
      • PolyRegression_ModelClass.gp_size_sg()
      • PolyRegression_ModelClass.gp_to_str()
      • PolyRegression_ModelClass.likelihood()
      • PolyRegression_ModelClass.loglikelihood()
    • beta_tuple
      • beta_tuple.beta
      • beta_tuple.size_sg
  • pysubgroup.numeric_target module
    • GeneralizationAware_StandardQFNumeric
      • GeneralizationAware_StandardQFNumeric.aggregate_statistics()
      • GeneralizationAware_StandardQFNumeric.evaluate()
    • NumericTarget
      • NumericTarget.calculate_statistics()
      • NumericTarget.get_attributes()
      • NumericTarget.get_base_statistics()
      • NumericTarget.statistic_types
    • StandardQFNumeric
      • StandardQFNumeric.a
      • StandardQFNumeric.invert
      • StandardQFNumeric.estimator
      • StandardQFNumeric.centroid
      • StandardQFNumeric.Max_Estimator
      • StandardQFNumeric.MeanOrdering_Estimator
      • StandardQFNumeric.Summation_Estimator
      • StandardQFNumeric.calculate_constant_statistics()
      • StandardQFNumeric.calculate_statistics()
      • StandardQFNumeric.evaluate()
      • StandardQFNumeric.mean_tpl
      • StandardQFNumeric.median_tpl
      • StandardQFNumeric.optimistic_estimate()
      • StandardQFNumeric.standard_qf_numeric()
      • StandardQFNumeric.tpl
    • StandardQFNumericMedian
      • StandardQFNumericMedian.tpl
    • StandardQFNumericTscore
      • StandardQFNumericTscore.calculate_constant_statistics()
      • StandardQFNumericTscore.calculate_statistics()
      • StandardQFNumericTscore.evaluate()
      • StandardQFNumericTscore.optimistic_estimate()
      • StandardQFNumericTscore.t_score()
      • StandardQFNumericTscore.tpl
    • calc_sorted_median()
    • read_mean()
    • read_median()
  • pysubgroup.permutation_test module
    • NegativeClassCountRandomSelector
      • NegativeClassCountRandomSelector.covers()
      • NegativeClassCountRandomSelector.select()
      • NegativeClassCountRandomSelector.selectors
      • NegativeClassCountRandomSelector.set_descriptions()
    • permutation_test()
  • pysubgroup.refinement_operator module
    • RefinementOperator
    • StaticGeneralizationOperator
      • StaticGeneralizationOperator.refinements()
    • StaticSpecializationOperator
      • StaticSpecializationOperator.refinements()
  • pysubgroup.representations module
    • BitSetRepresentation
      • BitSetRepresentation.Conjunction
      • BitSetRepresentation.Disjunction
      • BitSetRepresentation.patch_classes()
      • BitSetRepresentation.patch_selector()
    • BitSet_Conjunction
      • BitSet_Conjunction.append_and()
      • BitSet_Conjunction.compute_representation()
      • BitSet_Conjunction.n_instances
      • BitSet_Conjunction.size_sg
    • BitSet_Disjunction
      • BitSet_Disjunction.append_or()
      • BitSet_Disjunction.compute_representation()
      • BitSet_Disjunction.size_sg
    • NumpySetRepresentation
      • NumpySetRepresentation.Conjunction
      • NumpySetRepresentation.patch_classes()
      • NumpySetRepresentation.patch_selector()
    • NumpySet_Conjunction
      • NumpySet_Conjunction.all_set
      • NumpySet_Conjunction.append_and()
      • NumpySet_Conjunction.compute_representation()
      • NumpySet_Conjunction.size_sg
    • RepresentationBase
      • RepresentationBase.patch_all_selectors()
      • RepresentationBase.patch_classes()
      • RepresentationBase.patch_selector()
      • RepresentationBase.undo_patch_classes()
    • SetRepresentation
      • SetRepresentation.Conjunction
      • SetRepresentation.patch_classes()
      • SetRepresentation.patch_selector()
    • Set_Conjunction
      • Set_Conjunction.all_set
      • Set_Conjunction.append_and()
      • Set_Conjunction.compute_representation()
      • Set_Conjunction.size_sg
  • pysubgroup.subgroup_description module
    • BooleanExpressionBase
      • BooleanExpressionBase.append_and()
      • BooleanExpressionBase.append_or()
    • Conjunction
      • Conjunction.append_and()
      • Conjunction.append_or()
      • Conjunction.covers()
      • Conjunction.depth
      • Conjunction.from_str()
      • Conjunction.pop_and()
      • Conjunction.pop_or()
      • Conjunction.selectors
    • DNF
      • DNF.append_and()
      • DNF.append_or()
      • DNF.pop_and()
    • Disjunction
      • Disjunction.append_and()
      • Disjunction.append_or()
      • Disjunction.covers()
      • Disjunction.selectors
    • EqualitySelector
      • EqualitySelector.attribute_name
      • EqualitySelector.attribute_value
      • EqualitySelector.compute_descriptions()
      • EqualitySelector.covers()
      • EqualitySelector.from_str()
      • EqualitySelector.selectors
      • EqualitySelector.set_descriptions()
    • IntervalSelector
      • IntervalSelector.attribute_name
      • IntervalSelector.compute_descriptions()
      • IntervalSelector.compute_string()
      • IntervalSelector.covers()
      • IntervalSelector.from_str()
      • IntervalSelector.lower_bound
      • IntervalSelector.selectors
      • IntervalSelector.set_descriptions()
      • IntervalSelector.upper_bound
    • NegatedSelector
      • NegatedSelector.attribute_name
      • NegatedSelector.covers()
      • NegatedSelector.selectors
      • NegatedSelector.set_descriptions()
    • SelectorBase
      • SelectorBase.set_descriptions()
    • create_nominal_selectors()
    • create_nominal_selectors_for_attribute()
    • create_numeric_selectors()
    • create_numeric_selectors_for_attribute()
    • create_selectors()
    • get_cover_array_and_size()
    • get_size()
    • pandas_sparse_eq()
    • remove_target_attributes()
  • pysubgroup.utils module
    • BaseTarget
      • BaseTarget.all_statistics_present()
    • SubgroupDiscoveryResult
      • SubgroupDiscoveryResult.to_dataframe()
      • SubgroupDiscoveryResult.to_descriptions()
      • SubgroupDiscoveryResult.to_latex()
      • SubgroupDiscoveryResult.to_table()
    • add_if_required()
    • conditional_invert()
    • count_bits()
    • create_subgroup_with_representation()
    • derive_effective_sample_size()
    • equal_frequency_discretization()
    • find_set_bits()
    • float_formatter()
    • intersect_of_ordered_list()
    • is_categorical_attribute()
    • is_numerical_attribute()
    • minimum_required_quality()
    • overlap()
    • perc_formatter()
    • powerset()
    • prepare_subgroup_discovery_result()
    • remove_selectors_with_attributes()
    • results_df_autoround()
    • str_to_bool()
    • to_bits()
  • pysubgroup.visualization module
    • plot_distribution_numeric()
    • plot_npspace()
    • plot_qualities_on_sample_distribution()
    • plot_roc()
    • plot_sgbars()
    • similarity_dendrogram()
    • similarity_sgs()
    • supportSetVisualization()
  • Module contents