subgroups.algorithms package

Subpackages

• subgroups.algorithms.subgroup_lists package
  • Submodules
  • subgroups.algorithms.subgroup_lists.dslm module
    • DSLM
      • DSLM.fit()
      • DSLM.maximum_negative_overlap
      • DSLM.maximum_positive_overlap
  • subgroups.algorithms.subgroup_lists.gmsl module
    • GMSL
      • GMSL.INPUT_LINE_REGEX_PATTERN
      • GMSL.beta
      • GMSL.fit()
      • GMSL.input_file_path
      • GMSL.max_sl
      • GMSL.output_file_path
  • subgroups.algorithms.subgroup_lists.psld module
    • PSLD
      • PSLD.fit()
      • PSLD.sl_max_size
• subgroups.algorithms.subgroup_sets package
  • Submodules
  • subgroups.algorithms.subgroup_sets.bsd module
    • BSD
      • BSD.fit()
      • BSD.max_depth
      • BSD.minimum_support
      • BSD.num_subgroups
      • BSD.quality_measure
      • BSD.selected_subgroups
      • BSD.unselected_subgroups
      • BSD.visited_subgroups
  • subgroups.algorithms.subgroup_sets.cbsd module
    • CBSD
  • subgroups.algorithms.subgroup_sets.cpbsd module
    • CPBSD
  • subgroups.algorithms.subgroup_sets.qfinder module
    • QFinder
      • QFinder.fit()
      • QFinder.selected_subgroups
      • QFinder.test_subgroups()
      • QFinder.top_patterns
      • QFinder.unselected_subgroups
      • QFinder.visited_subgroups
  • subgroups.algorithms.subgroup_sets.sdmap module
    • SDMap
      • SDMap.additional_parameters_for_the_quality_measure
      • SDMap.fit()
      • SDMap.minimum_fp
      • SDMap.minimum_n
      • SDMap.minimum_quality_measure_value
      • SDMap.minimum_tp
      • SDMap.quality_measure
      • SDMap.selected_subgroups
      • SDMap.unselected_subgroups
      • SDMap.visited_nodes
  • subgroups.algorithms.subgroup_sets.sdmapstar module
    • SDMapStar
      • SDMapStar.additional_parameters_for_the_quality_measure
      • SDMapStar.conditional_pruned_branches
      • SDMapStar.fit()
      • SDMapStar.k_subgroups
      • SDMapStar.minimum_fp
      • SDMapStar.minimum_n
      • SDMapStar.minimum_quality_measure_value
      • SDMapStar.minimum_tp
      • SDMapStar.num_subgroups
      • SDMapStar.optimistic_estimate
      • SDMapStar.pruned_subgroups
      • SDMapStar.quality_measure
      • SDMapStar.selected_subgroups
      • SDMapStar.unselected_subgroups
      • SDMapStar.visited_nodes
  • subgroups.algorithms.subgroup_sets.vlsd module
    • VLSD
      • VLSD.SORT_CRITERION
      • VLSD.SORT_CRITERION_NO_ORDER
      • VLSD.SORT_CRITERION_QUALITY_ASCENDING
      • VLSD.SORT_CRITERION_QUALITY_DESCENDING
      • VLSD.VERTICAL_LISTS_IMPLEMENTATION
      • VLSD.VERTICAL_LISTS_WITH_BITSETS
      • VLSD.VERTICAL_LISTS_WITH_SETS
      • VLSD.additional_parameters_for_the_optimistic_estimate
      • VLSD.additional_parameters_for_the_quality_measure
      • VLSD.fit()
      • VLSD.oe_minimum_threshold
      • VLSD.optimistic_estimate
      • VLSD.q_minimum_threshold
      • VLSD.quality_measure
      • VLSD.selected_subgroups
      • VLSD.sort_criterion_in_other_sizes
      • VLSD.sort_criterion_in_s1
      • VLSD.unselected_subgroups
      • VLSD.visited_nodes

Submodules

subgroups.algorithms.algorithm module

This file contains the implementation of the root class of all implemented algorithms. This class is an abstract class and cannot be instantiated.

class subgroups.algorithms.algorithm.Algorithm

Bases: ABC

This abstract class defines the root class of all implemented algorithms.

abstract fit(pandas_dataframe, target)

Main method to run the corresponding algorithm.

Parameters:

• pandas_dataframe (pandas.core.frame.DataFrame) – the DataFrame which is scanned.

• target (tuple[str, str]) – a tuple with 2 elements: the target attribute name and the target value.

Return type:

None