def Main(filename,
features_file,
Algorithms,
number_of_features,
filter_target,
list_features=None):
print("\n---------------------------------\n")
print("Load Data", end="")
DATA = Load_Data.load_data(filename,
ALGORITHMS,
filter_target=filter_target)
print(" [OK]\nLoad ELA Features", end="")
P, D, F = Load_Data.load_ELA_features(features_file)
print(" [OK]\nLink ELA Features to problems", end="")
Problem.link_all_features(DATA, P, D, F)
print(" [OK]\nInitialize Empirical Performance Model", end="")
model = epm.EmpiricalPerformanceModel(
number_of_parameters,
number_of_features,
len(ALGORITHMS),
input_type="parameters",
selector=Selector.Random_selector(probability=0.7),
list_features=list_features)
print(" [OK]\nFix Training and Testing sets", end="")
model.build_training_and_testing_sets(DATA)
print("\nNumber of problems : " + str(len(model.get_results())) + "\n")
'''
print(" [OK]\nTrain EPM",end="")
model.train_model()
print(" [OK]\nTest EPM",end="")
model.test_model()
print(" [OK]\n")
SBS=Statistic.SingleBestSolver(model)
VBS=Statistic.VirtualBestSolver(model)
RS=Statistic.RealSolver(model)
Merit=Statistic.Merit(SBS,VBS,RS)
print("SBS "+str(SBS))
print("VBS "+str(VBS))
print("RS "+str(RS))
print("Merit "+str(Merit))
'''
model.reset_model()
model.set_input_type('features')
print("Train EPM", end="")
model.train_model()
print(" [OK]\nTest EPM", end="")
model.test_model()
print(" [OK]\n")
SBS = Statistic.SingleBestSolver(model)
VBS = Statistic.VirtualBestSolver(model)
RS = Statistic.RealSolver(model)
Merit = Statistic.Merit(SBS, VBS, RS)
print("SBS " + str(SBS))
print("VBS " + str(VBS))
print("RS " + str(RS))
print("Merit " + str(Merit))
def __init__(self,
number_of_parameters,
numberOfFeatures,
numberOfAlgorithms,
input_type="features",
learning_method=Learning_method.classical_forestRegression(),
selector=Selector.Random_selector(probability=0.2),
list_features=None):
self.numberOfFeatures = numberOfFeatures
self.list_features = list_features
self.number_of_parameters = number_of_parameters
self.set_input_type(input_type)
self.numberOfAlgorithms = numberOfAlgorithms
self.input_type = input_type
self.selector = selector
self.learning_method = learning_method
