Extensive comparisons have shown that support vector machines obtain good generalization performance on various data sets.
大量的对比实验已经表明支持向量机在很多问题上获得了良好的推广能力。
Parameter tuning of Support Vector Regression (SVR) has been a critical task to develop a SVR model with good generalization performance.
在回归支持向量机的建模中，参数调节问题一直是影响模型性能的重要因素之一。
Because of its strict mathematical theory of support and good generalization performance, it addresses the problem of small sample study of particular advantage.
由于它有严格的数学理论支撑以及较强的泛化性能，它在解决小样本学习问题时尤其具有优势。
SVM has been applied to many fields such as pattern recognition, data mining, modeling and control of nonlinear system due to good generalization ability and globally optimal performance.
SVM由于其良好的泛化能力和全局最优性能，在模式识别、数据挖掘、非线性系统建模和控制等领域中展现出广泛的应用前景。
The results of test show that the presented classifier has good performance on memory and generalization. The accuracy can be compared with many traditional methods.
实验结果表明，所提出的新型分类器具有良好的记忆和泛化性能，准确率可以与许多传统方法相比较。
The SVM method is based on seeking on the Structural Risk Minimization by few learning samples supporting, and it has important feature such as good generalization and classification performance, etc.
支持向量机方法基于小学习样本条件下，通过寻求结构风险最小，以期获得良好的分类效果和泛化能力。
Support Vector machine is a new machine-learning method and has its unique advantages in pattern recognition because of outstanding learning performance and good capabilities in generalization.
支持向量机是一种全新的机器学习方法，其出色的学习性能和泛化能力强等方面的优势，在模式识别领域中有其独到的优越性。
Especially, SVM based relevance feedback greatly improve the performance of retrieval system with its good generalization.
特别是基于支持向量机的相关反馈，由于具有良好的泛化能力，因而进一步提高了检索性能。
Simulation results for artificial data show that the proposed method gives good performance on reducing the effects of noise and improves the regression accuracy and generalization.
仿真实验结果显示了该方法有效地减少了噪声的影响，改进了回归的精度，增强了推广能力。
This VC dimension should be finite and small to guarantee the good performance of the generalization function.
VC维应当是有限而且小以确保具有好的推广性。
SVM has been wildly used for object detection and recognition for the past decades, because of its good generalization ability and performance.
近十年来，支持向量机因其通用性和良好的性能，被广泛地用于对象检测与识别。
Simulation results for both artificial and real data show the generalization performance of our method is a good approximation of SVMs and the computation complexity is largely reduced by our method.
文中最后对人工和实际样本进行了实验，结果说明了线性规划支撑矢量机在推广能力上较好地逼近了原支撑矢量机，而在计算复杂度上明显低于原支撑矢量机。
The wavelet neural network, which has good approximation and generalization performance in nonlinear modeling, is used to predict the final settlements of soft ground in expressway.
利用小波神经网络在非线性建模中的收敛迅速等优越性 ，提出利用小波神经网络预测高速公路软土地基的最终沉降量的方法。
The wavelet neural network, which has good approximation and generalization performance in nonlinear modeling, is used to predict the final settlements of soft ground in expressway.
利用小波神经网络在非线性建模中的收敛迅速等优越性 ，提出利用小波神经网络预测高速公路软土地基的最终沉降量的方法。
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