http://stackoverflow.com/questions/9390337/nnet-function-in-r

打不开网址
里面讲的什么？

decay: parameter for weight decay. Default 0.

Further information is available in the authors' book, Modern Applied Statistics with S. Fourth Edition, page 245:

One way to ensure that f is smooth is to restrict the class of estimates, for example, by using a limited number of spline knots. Another way is regularization in which the fit criterion is altered to

E + λC(f)

with a penalty C on the ‘roughness’ of f . Weight decay, specific to neural networks, uses as penalty the sum of squares of the weights wij. ... The use of weight decay seems both to help the optimization process and to avoid over-fitting. (emphasis added)

现在同时在用Matlab和R实现神经网络，Matlab用的newff、train、sim等函数；R用的nnet函数。但发现比较Matlab实现的算法用来分类的准确率无法和R比较，因为参数设置无法进行统一，比如输出层的神经元个数，Matlab可以设置，R不知道怎么设置，以及每层的激活函数，无法保证Matlab和R完全相同。R用什么包可以设置Matlab实现的神经网络的参数？