cross-validation
英 [krɒs ˌvælɪˈdeɪʃən]
美 [krɔːs ˌvæləˈdeɪʃən]
网络 交叉检验; 交叉验证; 交叉验证法; 验证法; 交叉证实
双语例句
- Design of RBF Network Based on cross-validation method
基于交叉验证的改进RBF分类器设计 - In NDA submissions, information about cross-validation study data, if applicable.
如适用，在新药申请中，交叉验证研究数据的信息。 - Solving the Regularization Parameters Based on Genetic Algorithms and the Generalized Cross-Validation Criterion
基于遗传算法和广义交叉原理求解正则参数 - We have applied holdout method and 10-fold cross-validation method in the system. They estimate mainly the accuracy rate of the model.
本系统实现的是保持法和10折交叉确认法，主要是对生成的决策树模型进行准确率方面的评估。 - Conclusion Cross-validation is relatively broadly applicable to the complicated model selection.
结论交互证实在复杂的模型选择中有较为广阔的应用前景。 - The cross-validation was calculated, demonstrating that the model was steady.
通过交叉验证，证明手性拓扑指数所得到的数学模型是稳定的。 - To evaluate the performance of the obtained model the cross-validation strategy was employed.
为了评价所得模型的行为，使用了交叉验证法。 - In this paper, some problems about smoothing factor selected by cross-validation technique are discussed and tested by using the simulation data.
本文对交叉证认技术选取平滑因子的若干问题进行了探讨，许采用模拟数据的方式验证了作者的观点。 - Hv-Block Cross-Validation Method for Hydrological Model Calibration
hv-block交叉验证法在率定水文模型参数中的比较研究 - Cross-validation method is used to estimate the number of principal component in X-ray fluorescence analysis.
本文报道了在X-射线荧光分析多变元体系因素分析中，应用交互有效法选择体系主组份的研究。 - This paper pointed out the disadvantages of the spilt-sample validation method and introduced the hv-block cross-validation method for the hydrological model calibration.
本文指出了应用分离样本验证法率定水文模型参数的不足，引入并探讨了hv-block交叉验证法的适用性，并与分离样本验证法进行比较。 - Compared with the BP neural network method only using the amino acid composition as features, the average absolute errors for cross-validation test are relatively reduced by 0.024 and 0.016 with the standard deviations reduced by 0.031 and 0.018, respectively.
与仅以氨基酸组成为特征矢量的BP神经网络方法比较，相应的他检验平均绝对误差分别减小了0.024和0.016，标准偏差分别减小了0.031和0.018； - The grid search and the pattern search were combined as an optimization strategy to optimize the three parameters of the SVM load model, and the more objective and effective cross-validation technique was introduced to train and assess the model.
参数优化时采用了结合网格搜索和模式搜索的组合寻优策略优化支持向量机负荷模型的3个参数，并且引入更加客观高效的交叉验证技术参与模型的训练和评价。 - This article presents basic principle of cross-validation and introduces a support-finding approach based on CV principle.
文中介绍了CV（CrossValidation）的基本原理，给出了一种基于CV原理的支持域确定方法的详细步骤； - It combines fast optimal brain surgeon, dynamic optimization of learning parameters and fast cross-validation.
这种启迪方法综合采用了快速自顶向下优化神经网络结构算法、动态优化学习参数算法和快速交叉校验算法。 - Choosing proper Kriging model, verifying of the Cross-Validation and correcting the parameters are important factors influencing accurate analysis.
分析中还发现Kriging插值模型的选择及Crossin&ValNation交叉验证的检验与系数修正均影响分析工作的结果精度。 - A leave-one-out cross-validation method was used to select the number of latent variables for the building of the QSAR models by principal component regression ( PCR) and partial least square regression ( PLS) method respectively.
然后分别采用主成分回归（PCR）和偏最小二乘回归（PLS）方法，通过留一法交叉验证选择潜变量个数，建立具有较好预测能力的定量构效关系（QSAR）模型。 - This type of designs is useful for computer experiments with qualitative and quantitative factors, multiple experiments, data pooling and cross-validation.
这种设计对具有定性和定量因子的计算机试验、多精度试验、数据整合和交叉验证很有用。 - All the feature vectors were divided to training set and testing set with Cross-validation method for classification and prediction, using BP neural network, wavelet neural network and support vector machine with different kernel functions.
利用交叉检验方法将所有特征向量分成训练集和测试集，使用了BP神经网络、小波神经网络和不同核函数的支持向量机进行分类的训练和测试，最后对测试的结果进行了比较和分析。 - The first implementation is the on-line estimator of source numbers improved from the cross-validation technique.
首先是在线信源数目估计器，它是通过改进交叉验证算法来实现的。 - Using the sample 2 to test the validity and reliability of the revised instruments for testing the cross-validation.
用样本2对修订的测量工具再次进行验证，来检验测量工具结构模型的复核效度。 - Through the cycle of experimental methods, radial basis function was chosen as the kernel function prediction model; and through the cross-validation method, the best parameters are determined.
采用循环实验的方法，选择了径向基核函数作为预测模型的核函数；又通过交叉验证的方法，确定了最佳参数。 - Compared the nonlinear least squares algorithm and genetic algorithm based on cross-validation. At last chose nonlinear least squares algorithm to identify the parameters of train brake model.
采用交互检验的方法分析比较了非线性最小二乘算法和遗传算法，最后在列车制动模型的基础上，选用非线性最小二乘算法对列车制动参数进行辨识。 - For the independent test and cross-validation, the good prediction results were also obtained.
同时在交叉检验和独立测试下都得到了较好的预测效果。 - Before SVM classifier application, a set of data was used for training, the use of cross-validation and grid search techniques to optimize the SVM RBF kernel parameters. Afterward tomato picture was took for the SVM classifier to recognition experiments.
在应用SVM分类器之前，先用样本数据进行训练，运用交叉验证和网格搜索技术优化SVM的RBF核函数参数，然后拍摄番茄图像用于SVM分类器识别实验，分析实验结果，并提出了多类识别方向。 - They are tested by cross-validation with a real data set according to Minimum Overall Risk rule, and compared with classification results of neural networks and Bayesian networks model with Minimum Probability of Error rule.
在真实数据集上按最小总风险准则采用交叉验证对贝叶斯网络信用评估模型进行了测试，并与按最小错误概率准则的神经网络、贝叶斯网络分类模型的结果进行了对比。 - The raw spectra were pretreated by the second derivative and smoothing, prediction models were established by using RBF, the models were validated using Leave-one-out cross-validation approach, and the influence of parameters was discussed.
对原始光谱进行平滑和二阶导数处理，用RBF神经网络法建模，采用Leave-one-out交叉验证法对模型进行验证，并对参数的影响进行了讨论。 - Then Cross-Validation method which is based on statistical learning is introduced for confirming the best classification parameter. 4.
并采用基于统计学习的交叉验证法确定了最佳SVM分类参数。 - Training and identifying SVM by selecting Gaussian kernel function and polynomial kernel function and using cross-validation method, the optimal parameter model is obtained and the significant experimental results are achieved, which lay a good foundation for further studies.
选择了高斯核函数和多项式核函数，应用交叉验证的方法对SVM进行训练识别，得到了最优的参数模型，取得了有一定意义的实验结果，为进一步的研究奠定了较好的基础。 - Through cross-validation and prediction set, the external examination results show that the model have a good stability and predictive ability.
通过交叉验证和对预测集进行外部检验，结果显示模型具有很好的稳定性和预测能力。