def __init__(self, scoring_function: Scoring, normaliser: Normaliser=None, folds: int=1):
    df = pandas.read_csv('./winequality-red.csv', sep=';', usecols=['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar', 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density', 'pH', 'sulphates', 'alcohol', 'quality'])
    data = np.array(df[['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar', 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density', 'pH', 'sulphates', 'alcohol']])
    target = np.array(df['quality'])
    super(RedWineQualityPredictionProblem, self).__init__(Objective.Minimisation, 'Red Wine Quality Prediction', data_x=data, target_x=target, normaliser=normaliser, folds=folds, scoring_function=scoring_function)
def __init__(self, scoring_function: Scoring, normaliser: Normaliser=None, folds: int=1):
    df = pandas.read_csv('./winequality-red.csv', sep=';', usecols=['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar', 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density', 'pH', 'sulphates', 'alcohol', 'quality'])
    data = np.array(df[['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar', 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density', 'pH', 'sulphates', 'alcohol']])
    target = np.array(df['quality'])
    super(RedWineQualityPredictionProblem, self).__init__(Objective.Minimisation, 'Red Wine Quality Prediction', data_x=data, target_x=target, normaliser=normaliser, folds=folds, scoring_function=scoring_function)