def run_msdp_train(moea, targets, predict_model):
moea_name = dictionaries.get_moea_name(moea)
predict_model_name = dictionaries.get_model_method_name(predict_model)
targets_name = dictionaries.get_target_composition(targets)
folder_name = 'multi-objective/' + predict_model_name + '/' + moea_name + '/' + targets_name
l = -20
u = 20
helpers.training_record_for_msdp(save_folder=folder_name,
target=targets,
predict_model=predict_model,
l=l,
u=u,
moea=moea)
def run_msdp_fpa_l1_nsga2_toZero_train():
save_file = '多目标优化_FPA+L1_nsga2_toZero'
target = [0, 3]
predict_model = 'linear'
l = -20
u = 20
maxgen = 100
drawing = 0
moea = 3
helpers.training_record_for_msdp(save_file=save_file,
target=target,
predict_model=predict_model,
l=l,
u=u,
moea=moea,
drawing=drawing,
maxgen=maxgen)
def run_msdp_fpa_aae_nonz_nsga2_DE_toZero_train():
save_file = '多目标优化_FPA+AAE+numofnonzero_nsga2_DE_toZero'
target = [0, 1, 2]
predict_model = 'linear'
l = -20
u = 20
maxgen = 100
drawing = 0
moea = 4
helpers.training_record_for_msdp(save_file=save_file,
target=target,
predict_model=predict_model,
l=l,
u=u,
moea=moea,
drawing=drawing,
maxgen=maxgen)
def run_msdp_FPA_L1_MSE_train(moea):
target_name = 'FPA_L1_MSE'
save_file = dictionaries.get_moea_name(moea) + '/' + target_name
target = [0, 3, 4]
predict_model = 'linear'
l = -20
u = 20
maxgen = 100
drawing = 0
moea = moea
helpers.training_record_for_msdp(save_file=save_file,
target=target,
predict_model=predict_model,
l=l,
u=u,
moea=moea,
drawing=drawing,
maxgen=maxgen)