def run():
problem = AckleyProblem()
try:
solver = AIS(chromosome=AckleyChromosome(dimensions=10),
problem=problem,
population_size=100,
epochs=100,
policies=[
Policy.EnforceLimitedMutationAttempts,
Policy.EnforceUniqueChromosome
],
duration=None)
best_chromosome = solver.run()
problem.log_chromosome(best_chromosome, solver)
except Exception as ex:
application_logger.exception(
exc_info=ex,
msg="Exception occurred whilst attempting to solve {}".format(
problem.name))
def run():
try:
problem = BostonHousingProblem(
scoring_function=Scoring.MeanAbsoluteError,
normaliser=Normaliser.RobustScaler,
folds=2)
"""
Regressor choices:
- AdaBoostRegressorChromosome
- DecisionTreeRegressorChromosome
- GradientBoostingRegressorChromosome
- KNeighborsRegressorChromosome
- MLPRegressorChromosome
- RandomForestRegressorChromosome
- XGBRegressorChromosome
"""
solver = AIS(chromosome=GradientBoostingRegressorChromosome(),
problem=problem,
population_size=20,
epochs=-1,
policies=[
Policy.EnforceLimitedMutationAttempts,
Policy.EnforceUniqueChromosome
],
duration=None)
best_chromosome = solver.run()
problem.log_chromosome(best_chromosome, solver)
except Exception as ex:
application_logger.exception(msg="", exc_info=ex)
def run():
"""
The OneMax problem represents a classical optimisation problem where the
chromosome is represented as a list of 1s an 0s and the quality of the
chromosome is evaluated by the sum of it's alleles.
"""
problem = OneMaxProblem()
try:
"""
The Artificial Immune System is a bio inspired evolutionary method and
is used here to demonstrate the application of the framework to the
OneMax problem.
"""
solver = AIS(chromosome=OneMaxChromosome(dimensions=100),
problem=problem,
population_size=100,
epochs=100,
policies=[
Policy.EnforceLimitedMutationAttempts,
Policy.EnforceUniqueChromosome
],
duration=None)
best_chromosome = solver.run()
problem.log_chromosome(best_chromosome, solver)
except Exception as ex:
application_logger.exception(
exc_info=ex,
msg="Exception occurred whilst attempting to solve the {}".format(
problem.name))