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泛化能力

网络Generalization; generalization ability; generalization capability

泛化能力

泛化能力

泛化能力

Generalization

提高学习算法的泛化能力 ( generalization) 一直是监督分类的重要研究内容 ,高精度的预测结果也是应用的不断需求[ 2 ] 。由于 …

generalization ability

f 提高泛化能力（generalization ability）是机器学习中最重要的问题之一。泛化能力表征了机器学习系统对新事件的适用性，简 …

generalization capability

在对神经网络的研究中 ,网络的泛化能力 ( Generalization capability) 是衡量其网络性能好坏的重要标志 ,而从实际应用中得出的 …

generalization performance

泛化特征值,general... ... ) generalization “泛化” ) generalization performance 泛化能力 ) generalization ability 泛化能力 ...

generalization capacity

泛化能力... ... ) generalization performance 泛化能力 ) generalization capacity 泛化能力 ) High Generalization 高泛化能力 ...

peneralization capability

为了达到好的近似(approximation)和泛化能力(peneralization capability)，他决定藉由确认平均相关性来决定子空间的数量，这 …

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The application result shows that the prediction with this method can achieve higher robust, better utility and expensive value .

通过对现场实际数据进行仿真，表明该方法鲁棒性强，准确性高，泛化能力广，具有很强的实用性和推广价值。

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The prediction results indicate that the sales forecast precision is improved, the capability of generalization is good .

仿真结果表明，该模型预测精度较高，具有较好的泛化能力。

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The simulations indicate that generalization ability of the RBF network can be improved a lot.

仿真表明这种算法可以显著提高传统 RBF 网络的泛化能力。

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Aiming at the conflict between recognition accuracy and generalization ability .

在覆盖算法中，识别精度与泛化能力之间存在矛盾。

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The simulation results illustrate the proposed method has well ability for prediction and generalization .

仿真实验表明该模型具有良好的预测能力和泛化能力。

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Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.

核函数是 SVM 的关键技术，核函数的选择将影响着支持向量机的学习能力和泛化能力。

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The BP neural network is adopted to realize the reinforcement learning to strengthen the generalization ability .

应用 BP 神经网络实现强化学习，以增强系统的泛化能力；

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Illustrating from experiments , the model has a high prediction precision , and good generalization ability .

实验表明，基于 GEP 技术得到的私人汽车拥有量模型预测精度高、泛化能力强。

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The correctness , reactiveness and the ability of generalization of the algorithm are verified by simulation tests.

经仿真验证，算法正确有效，具有良好的收敛性和泛化能力。

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By the analysis of X-ray image distortion , this paper presents a neural network system correction method based on global optimization.

通过对 X 光图像所产生畸变的分析，提出了一种基于泛化能力的神经网络系统整体校正方法。

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