Computer/NN_Trainer/Util.py
def splitTrainTestVal(x, y, testVal_size):
    '''
    splits data into train, test, and validation data sets
    :param x: input data
    :param y: output data
    :return: (x_train, x_test, x_val, _train, y_test, y_val)
    '''
    x_train, x_testVal, y_train, y_testVal = train_test_split(x, y, test_size=testVal_size, random_state=42)
    x_test, x_val, y_test, y_val = train_test_split(x_testVal, y_testVal, test_size=0.5,random_state=53)  # split the testVal into test and validation sets
    return x_train, x_test, x_val, y_train, y_test, y_val

    splits data into train, test, and validation data sets
    :param x: input data
    :param y: output data
    :return: (x_train, x_test, x_val, _train, y_test, y_val)
    
splits data into train, test, and validation data sets
splits data into train test and validation data sets
def splitTrainTestVal(x, y, testVal_size):
    x_train, x_testVal, y_train, y_testVal = train_test_split(x, y, test_size=testVal_size, random_state=42)
    x_test, x_val, y_test, y_val = train_test_split(x_testVal, y_testVal, test_size=0.5,random_state=53)  
    return x_train, x_test, x_val, y_train, y_test, y_val
def splitTrainTestVal ( x , y , testVal_size ) : x_train , x_testVal , y_train , y_testVal = train_test_split ( x , y , test_size = testVal_size , random_state = 42 ) x_test , x_val , y_test , y_val = train_test_split ( x_testVal , y_testVal , test_size = 0.5 , random_state = 53 ) return x_train , x_test , x_val , y_train , y_test , y_val
splits data into train, test, and validation data sets
splits data into train test and validation data sets
'''
    splits data into train, test, and validation data sets
    :param x: input data
    :param y: output data
    :return: (x_train, x_test, x_val, _train, y_test, y_val)
    ''' # split the testVal into test and validation sets
None
x
None
y
None
testVal_size