def scale_data(data):
    return MinMaxScaler().fit_transform(data[0]), data[1]

def prepare_cancer_data(data):
    points, labels = data
    return points, np.array([1 if label == 'M' else 0 for label in labels])

def prepare_sms_data(data):
    points, labels = data
    return points, np.array([1 if label == 'ham' else 0 for label in labels])

def data_split(data, test_size=0.2):
    points, labels = data
    train_points, test_points, train_labels, test_labels = train_test_split(points, labels, test_size=0.2)
    return (train_points, train_labels), (test_points, test_labels)


spam_data = scale_data(spam_data)
sms_data = prepare_sms_data(sms_data)
cancer_data = prepare_cancer_data(scale_data(cancer_data))

train_blob, test_blob = data_split(blob_data)
train_cancer, test_cancer = data_split(cancer_data)
train_spam, test_spam = data_split(spam_data)
train_sms, test_sms = data_split(sms_data)