在黄广斌教授文章《Extreme learning machine:Theory and application》中，他说“The traditional classic gradient-based learning algorithms may face several issues like local minima,improper learning rate and overfitting, etc. In order to avoid these issues, some methods such as weight decay and early stopping methods may need to be used often in these classical learning algorithms. The ELM tends to reach the solutions straightforward without such trivial issues“。就是说ELM不会存在局部最小值和过拟合问题，不存在局部最小值好理解，毕竟他的输入权值和偏置项是随机的。但是不会出现过拟合问题就理解不了，他的节点数如果多于达到误差允许的理想节点数，不一样会出现过拟合问题吗。求大佬指教指教。顿首再拜。