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【求助】急求：神经网络拟合非线性函数的问题！！！
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本人现在用 ”径向基神经网络“ 拟合一条类似于 ”指数曲线“ 的函数，拟合的相对误差小于2.5%，满足了实验的需要。网络的输入和输出向量都是一维的，样本容量为50。训练过程中，输入和输出向量经过log函数和归一化法预处理，并采用了留一法交叉验证。文章修回时，审稿人提出了许多的问题，有些很难回答，希望能得到神经网络高手的指点！我该如何回答这些问题呢？ 1. Certain authors claim an ANN should use at least 5 sample points per connection weight . I believe this is far away from the conditions used by the authors. How was this limitation circumvented by authors? 2. Is there a criteria to choose to normalize data in the interval [0,1] ? 3. Can the authors justify that total numeric range is narrowed and simultaneously the resulting values are uniformly weighed? 4. The use of leave-one-out cross validation implies that the overfitting must be taken into account. This is done in the case of lack of enough input data, given a single sample is excluded each time. In fact, a k-fold-cross validation is much more confident in this respect. Can the authors comment on this point? |
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