classes.optimizers package

Submodules

classes.optimizers.constraint_based_optimizer module

class classes.optimizers.constraint_based_optimizer.ConstraintBasedOptimizer(node_id: str, structure_estimator: classes.estimators.structure_estimator.StructureEstimator, tot_vars_count: int)

Bases: classes.optimizers.optimizer.Optimizer

Optimizer class that implement a CTPC Algorithm

Parameters

• node_id (string) – current node’s id

• structure_estimator (class:'StructureEstimator') – a structure estimator object with the information about the net

• tot_vars_count (int) – number of variables in the dataset

optimize_structure()

Compute Optimization process for a structure_estimator by using a CTPC Algorithm

Returns

the estimated structure for the node

Return type

List

classes.optimizers.hill_climbing_search module

class classes.optimizers.hill_climbing_search.HillClimbing(node_id: str, structure_estimator: classes.estimators.structure_estimator.StructureEstimator, max_parents: int = None, iterations_number: int = 40, patience: int = None)

Bases: classes.optimizers.optimizer.Optimizer

Optimizer class that implement Hill Climbing Search

Parameters

• node_id (string) – current node’s id

• structure_estimator (class:'StructureEstimator') – a structure estimator object with the information about the net

• max_parents (int, optional) – maximum number of parents for each variable. If None, disabled, default to None

• iterations_number (int, optional) – maximum number of optimization algorithm’s iteration, default to 40

• patience (int, optional) – number of iteration without any improvement before to stop the search.If None, disabled, default to None

optimize_structure() → List

Compute Optimization process for a structure_estimator by using a Hill Climbing Algorithm

Returns

the estimated structure for the node

Return type

List

classes.optimizers.optimizer module

class classes.optimizers.optimizer.Optimizer(node_id: str, structure_estimator: classes.estimators.structure_estimator.StructureEstimator)

Bases: abc.ABC

Interface class for all the optimizer’s child classes

Parameters

• node_id (string) – the node label

• structure_estimator (class:'StructureEstimator') – A structureEstimator Object to predict the structure

abstract optimize_structure() → List

Compute Optimization process for a structure_estimator

Returns

the estimated structure for the node

Return type

List

classes.optimizers.tabu_search module

class classes.optimizers.tabu_search.TabuSearch(node_id: str, structure_estimator: classes.estimators.structure_estimator.StructureEstimator, max_parents: int = None, iterations_number: int = 40, patience: int = None, tabu_length: int = None, tabu_rules_duration=None)

Bases: classes.optimizers.optimizer.Optimizer

Optimizer class that implement Tabu Search

Parameters

• node_id (string) – current node’s id

• structure_estimator (class:'StructureEstimator') – a structure estimator object with the information about the net

• max_parents (int, optional) – maximum number of parents for each variable. If None, disabled, default to None

• iterations_number (int, optional) – maximum number of optimization algorithm’s iteration, default to 40

• patience (int, optional) – number of iteration without any improvement before to stop the search.If None, disabled, default to None

• tabu_length (int, optional) – maximum lenght of the data structures used in the optimization process, default to None

• tabu_rules_duration (int, optional) – number of iterations in which each rule keeps its value, default to None

optimize_structure() → List

Compute Optimization process for a structure_estimator by using a Hill Climbing Algorithm

Returns

the estimated structure for the node

Return type

List

Module contents