LASSOとElasticNet-例(sklearn実装)

import numpy as np
from sklearn import linear_model

#        ，      
data = [[83.0, 234.289, 235.6, 159.0, 107.608, 1947., 60.323],
        [88.5, 259.426, 232.5, 145.6, 108.632, 1948., 61.122],
        [88.2, 258.054, 368.2, 161.6, 109.773, 1949., 60.171],
        [89.5, 284.599, 335.1, 165.0, 110.929, 1950., 61.187],
        [96.2, 328.975, 209.9, 309.9, 112.075, 1951., 63.221],
        [98.1, 346.999, 193.2, 359.4, 113.27, 1952., 63.639],
        [99.0, 365.385, 187., 354.7, 115.094, 1953., 64.989],
        [100.0, 363.112, 357.8, 335.0, 116.219, 1954., 63.761],
        [101.2, 397.469, 290.4, 304.8, 117.388, 1955., 66.019],
        [104.6, 419.18, 282.2, 285.7, 118.734, 1956., 67.857],
        [108.4, 442.769, 293.6, 279.8, 120.445, 1957., 68.169],
        [110.8, 444.546, 468.1, 263.7, 121.95, 1958., 66.513],
        [112.6, 482.704, 381.3, 255.2, 123.366, 1959., 68.655],
        [114.2, 502.601, 393.1, 251.4, 125.368, 1960., 69.564],
        [115.7, 518.173, 480.6, 257.2, 127.852, 1961., 69.331],
        [116.9, 554.894, 400.7, 282.7, 130.081, 1962., 70.551]]
data = np.array(data)
x_data = data[:, 1:]
y_data = data[:, 0]
print(x_data)
print(y_data)

#     ，    

# LASSO+       
lasso_model = linear_model.LassoCV()
lasso_model.fit(x_data, y_data)

#          
print(lasso_model.coef_)
# lasso  
print(lasso_model.alpha_)

#     
lasso_model.predict(x_data[3, np.newaxis])

#     ，    

# ElasticNet+       
elastic_model = linear_model.ElasticNetCV()
elastic_model.fit(x_data, y_data)

#          
print(elastic_model.coef_)
#      
print(elastic_model.alpha_)

#     
elastic_model.predict(x_data[3, np.newaxis])