loaded_data = FileManager.load_file(file_path)
output_filename = FileManager.create_output_file()
#rescaling_normalizer = RescalingNormalizer()
#scikit_normalizer = ScikitNormalizer()
#data_manager = DataManager(normalizer=scikit_normalizer)
data_manager = DataManager(normalizer=None)
data_manager.set_data(loaded_data)
data_manager.split_data(test_split=0.15, train_split=0.70)
model = svm.SVR()
population = Population()
population.load_data()
'''
TrainX, TrainY, ValidateX, ValidateY, TestX, TestY = FromDataFileMLR_DE_BPSO.getAllOfTheData()
TrainX, ValidateX, TestX = FromDataFileMLR_DE_BPSO.rescaleTheData(TrainX, ValidateX, TestX)
velocity = createInitVelMat(numOfPop, numOfFea)
def rescaleTheData(TrainX, ValidateX, TestX):
# 1 degree of freedom means (ddof) N-1 unbiased estimation
TrainXVar = TrainX.var(axis = 0, ddof=1)
TrainXMean = TrainX.mean(axis = 0)
