def learn_DNF__recombination():
dnf = DNF()
length = 58
epsilon = (2**-53)
tau = (epsilon / length)**3 * log(1 / epsilon)
tolerance = ConjunctionTolerance(length, epsilon)
conjunction_performance_oracle = OneSidedPerformanceOracleWithTolerance(
dnf, tau)
performance_oracle = DNFOneSidePerformanceOracleWithTolerance(
dnf, tau, epsilon, conjunction_performance_oracle)
mutation_neighborhood = MonotoneConjunctionNeighborhood()
recomb_rate = 0.176
natural_process = RecombinationProcess(recomb_rate)
neighborhood = NeighborhoodWithOtherRepresentations(
length, mutation_neighborhood, 0.1, natural_process)
recombinator = Recombinator(neighborhood, performance_oracle, tolerance,
epsilon)
algorithm = ConstantPopulationMutationConjunctionAlgorithm(
recombinator, length, epsilon, performance_oracle, 75)
print algorithm.learn_ideal_function_until_match()
def learn_single_time__HGT(common_classes):
neighborhood, performance_oracle, natural_process = get_params_for_mutator(common_classes)
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes()
population_size, population_factor = common_classes.get_population_size_and_factor()
HGT_mutator = HGT_Mutator(neighborhood, performance_oracle, tolerance, epsilon, natural_process)
algorithm = ConstantPopulationMutationConjunctionAlgorithm(HGT_mutator, length, epsilon, performance_oracle,
population_size, population_factor)
return algorithm.learn_ideal_function_until_match()
def learn_single_time__HGT(common_classes):
neighborhood, performance_oracle, natural_process = get_params_for_mutator(
common_classes)
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes(
)
population_size, population_factor = common_classes.get_population_size_and_factor(
)
HGT_mutator = HGT_Mutator(neighborhood, performance_oracle, tolerance,
epsilon, natural_process)
algorithm = ConstantPopulationMutationConjunctionAlgorithm(
HGT_mutator, length, epsilon, performance_oracle, population_size,
population_factor)
return algorithm.learn_ideal_function_until_match()
def learn_DNF__HGT():
dnf = DNF()
length = 58
epsilon = (2**-53)
tau = (epsilon / length)**3 * log(1/epsilon)
tolerance = ConjunctionTolerance(length, epsilon)
conjunction_performance_oracle = OneSidedPerformanceOracleWithTolerance(dnf, tau)
performance_oracle = DNFOneSidePerformanceOracleWithTolerance(dnf, tau, epsilon,
conjunction_performance_oracle)
mutation_neighborhood = MonotoneConjunctionNeighborhood()
natural_process = HGTProcess(0.176, length)
neighborhood = NeighborhoodWithOtherRepresentations(length, mutation_neighborhood,
0.1, natural_process)
HGT_mutator = HGT_Mutator(neighborhood, performance_oracle, tolerance, epsilon, natural_process)
algorithm = ConstantPopulationMutationConjunctionAlgorithm(HGT_mutator, length, epsilon, performance_oracle, 75)
print algorithm.learn_ideal_function_until_match()
