utils.py
def load_data_diabetes():
    """
    load the diabetes data with 10 predictors and 1 response
    :return: return input matrix x and response vector y
    """
    x = np.genfromtxt('data/diabetes.data', skip_header=1, dtype=float, usecols=range(10))
    y = np.genfromtxt('data/diabetes.data', skip_header=1, dtype=float, usecols=[10])
    return x, y

    load the diabetes data with 10 predictors and 1 response
    :return: return input matrix x and response vector y
    
load the diabetes data with 10 predictors and 1 response
load the diabetes data with 10 predictors and 1 response
def load_data_diabetes():
    x = np.genfromtxt('data/diabetes.data', skip_header=1, dtype=float, usecols=range(10))
    y = np.genfromtxt('data/diabetes.data', skip_header=1, dtype=float, usecols=[10])
    return x, y
def load_data_diabetes ( ) : x = np . genfromtxt ( 'data/diabetes.data' , skip_header = 1 , dtype = float , usecols = range ( 10 ) ) y = np . genfromtxt ( 'data/diabetes.data' , skip_header = 1 , dtype = float , usecols = [ 10 ] ) return x , y
load the diabetes data with 10 predictors and 1 response
load the diabetes data with 10 predictors and 1 response
"""
    load the diabetes data with 10 predictors and 1 response
    :return: return input matrix x and response vector y
    """
return input matrix x and response vector y
return input matrix x and response vector y