这是我的代码。当我运行它时,山脊很好,但是对于套索,我收到错误消息:
ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations.
请帮忙。
from sklearn.linear_model import LinearRegression, Lasso, Ridge, RidgeCV, LassoCV
from sklearn.model_selection import cross_val_score
import numpy as np
import sys
dataset = np.loadtxt(sys.argv[1], delimiter = ',')
X = dataset[:,:10]
y = dataset[:,10]
ridge_cv = RidgeCV(alphas=[1e-3, 1e-2, 1e-1, 1, 10, 100]).fit(X,y)
lasso_cv = LassoCV(alphas=[1e-3, 1e-2, 1e-1, 1, 10, 100]).fit(X,y)
lin_reg = LinearRegression()
ridge_reg = Ridge(alpha = ridge_cv.alpha_)
lasso_reg = Lasso(alpha = lasso_cv.alpha_)
print(cross_val_score(lin_reg, X, y, cv=2).mean())
print(cross_val_score(ridge_reg, X, y, cv=2).mean())
print(cross_val_score(lasso_reg, X, y, cv=2).mean())
最佳答案
关于python - Lasso 回归目标未收敛,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59396620/