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您好,练习5中的多项式特征大于2的时候,执行报错 X_poly, Xval_poly, Xtest_poly = prepare_poly_data(X, Xval, Xtest, power=8) plot_learning_curve(X_poly, y, Xval_poly, yval, l=0)
linear_regression_np(X[:i, :], y[:i], l=1) res = opt.minimize(fun=regularized_cost, x0=theta, args=(X, y, l), method='TNC', jac=regularized_gradient, options={'disp': True}) File "", line 1, in rc, nf, nit, x = moduleTNC.minimize(func_and_grad, x0, low, up, scale, ValueError: tnc: invalid return value from minimized function.
能帮忙看一下吗?
The text was updated successfully, but these errors were encountered:
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您好,练习5中的多项式特征大于2的时候,执行报错
X_poly, Xval_poly, Xtest_poly = prepare_poly_data(X, Xval, Xtest, power=8)
plot_learning_curve(X_poly, y, Xval_poly, yval, l=0)
能帮忙看一下吗?
The text was updated successfully, but these errors were encountered: