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1·BP network overfitting learning ability generalization ability uncertainty relation.

标签BP网络过拟合学习能力推广能力不确定关系。

2·That is, some branches of the tree that may lead to the model overfitting are cut off.

这就是说，树的某些导致模型过拟合的分支将被剪掉。

3·As an aside, some machine learning techniques use a fourth set of data, called a validation set, which is used during training to avoid overfitting.

另一方面，一些机器学习技术使用第四种数据集，称为验证集[validation set]，它被用来在整个训练期间避免过适合[overfitting]。

4·The problem is called overfitting: If we supply too much data into our model creation, the model will actually be created perfectly, but just for that data.

这个问题就是所谓的过拟合：如果我们提供过多 数据用于模型创建，我们的模型虽然会被完美创建，但只针对的是该数据。

5·This method is robust to Gaussian noise and constellation rotation due to initial phase of signal and avoids overfitting and local minimum in neural networks.

这种方法对高斯噪声和星座图由于信号初始相位而引入的旋转具有良好的稳健性，并避免了神经网络中的过学习和局部极小点等缺陷。

6·When solving this small sample problem with high dimension and nonlinear, many traditional pattern recognition methods will tend to occur overfitting phenomenon.

对于这样一个高维数、非线性的小样本问题， 许多传统的模式识别方法都容易出现过学习或欠学习现象。

7·A post pruning procedure is designed to deal with the overfitting problem, and two criteria that are the minimum covering rate and the minimum error rate are defined.

同时，基于最小覆盖率和最小错误率给出了一种克服过学习问题的后处理方法。

8·The very dense data sets that result from shotgun approaches on small numbers of patients carry a significant risk of model overfitting, leading to spurious associations.

这些密集的数据集是通过把散弹射击的方法应用在小规模病人而得到的。，但它带来一个有显著风险度的过于合适模型，导致假联系。

9·This, too, can lead to overfitting, and it is a challenge to find algorithms that are both powerful enough to learn complex functions and robust enough to produce generalizable results.

这一点也可能导致过适合。不但要在学习复杂函数时足够强大，而且能产生可概括的结论，寻找这样的算法的确是一个挑战。