如果您愿意的话为您的模型选择一个名字。
支持向量机的模型选择研究。
从现有基础模型选择正确的原型和模式并生成差异。
Selecting Proper Archetypes and Patterns and Generating Variations from the Existing Base models.
模型选择是支持向量机一个重要的研究方向。
最小二乘回归模型选择与九技术，包括逐步回归。
Least squares regression with nine model selection techniques, including stepwise regression.
本文证明了这种信息准则在模型选择方面具有一致性。
The consistency of BICC in high dimensional data model selection is also shown.
分析了面板数据模型的类型、参数估计和模型选择方法；
The type of panel data model, estimation of parameters and choose method of model will be analyzed.
并提出了针对不同类簇判断有效降维维数的模型选择准则。
The model selection principle of determining effective number of dimensionality reduction for different clusters is proposed.
但是，如何为模型选择特定数值的方法有可能带来一些问题。
But the way you pick the individual values to plug into the model can cause trouble.
在贝叶斯统计学中，贝叶斯因子是进行模型选择的主要工具。
Bayes factor is the major tool for model selection in Bayesian Statistics.
在建立模型过程中基于简便易行的AIC准则进行模型选择。
In the process of modeling, the choice of models was under the simple and feasible evaluation criterions of AIC.
然后为新模型选择一个模板，在目前情况下，选择包含空白物理模型的模板。
Then select a template for the new model, that, in this case, contains a new empty physical model.
由于抽样变异性和模型选择所引起的不确定性应在展示疾病负担结果的时候予以说明。
The uncertainty owing to both the sampling variability and the choice of model (s) should be given when disease burden results are presented.
AIC与SIC等准则函数方法是arma模型选择过程中经常使用的方法。
Several criteria such as AIC and SIC are usually used in ARMA model selection.
一个好的实验模型选择的主要准则之一，是模型中参数的估值应该是无偏的。
A fundamental criterion for selecting a proper model in specified experiment requires the unbiased estimates of parameters in the model.
首先，我们综述了基于贝叶斯阴阳机和谐学习原则的自动模型选择学习算法。
First, we summarize some amS learning algorithms on Gaussian or finite mixture based on the Bayesian Ying-Yang (BYY) harmony learning principle.
实验结果表明：经模型选择后的KICA能成功分离脑电信号中的心电伪差。
KICA with model selection step is applied to the task of removing ECG artifact from the EEG signal and the result shows KICA.
对线性网络的模型选择和多层前馈网络的关系做了细致的研究，并分别进行了仿真。
A delicate research about the relationship of the selection of model of the linear network part and the multi-layered feed-forward network part and simulation are presented.
贝叶斯模型平均法用来综合各模型的结果并提供一种反映模型选择和抽样变异性的不确定性度量。
Bayesian model averaging was used to combine the results across models and to provide a measure of uncertainty that reflects the choice of model and the sampling variability.
而且，针对无监督图像分割的模型选择问题提出了带惩罚项的误差平方和阶次判定准则。
Furthermore, in order to solve the model selection problems of unsupervised image segmentation, the sum of squared error criterion with penalty term is proposed.
这对数据模型选择上的冲击，反过来，是基于由生物学家提出的生物信息学数据的组织。
This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists.
递归预测法便于计算机实现，并进而进行预测模型发现，模型选择和预测的自动化工作。
Recursive forecasting method is easy to be implemented on computer and thus makes forecasting model discovery, model selection and forecasting automatic.
因而存在一个对各种方案过程模型选择的问题，这个问题可以转化为多目标模糊最短路径问题。
There exists a problem of selecting alternative process models, which can be transformed into a problem of multi-objective fuzzy shortest path.
模型选择的重点应该放在模型的自动选择上，实现模型的自动选择是智能决策的重要研究领域。
Emphasis of model selection exists in automatic selection of model and how to realize automatic selection is an important research domain in IDSS.
指出子空间信息准则是模型选择的一种新准则，它在一些假设条件下，给出推广误差的一种无偏估计。
Subspace information criterion is a new criterion for model selection, it gives an unbiased estimate for the generalization error under some assumptions.
作者用模型选择的方法提出了一种程序以估计转变点的个数及位置，然后建立了这些程序的强相合性。
The authors propose some procedure for estimating the number and locations of change points within the framework of model selection, and establish the strong consistency of these procedures.
给定源语言句子，系统在所有候选目标语言句子中，基于统计模型选择概率最大的句子作为翻译结果。
Given a source sentence, and based on the statistical model, the system selects the string with the highest probability by statistical model from all possible target sentences.
文章回顾了各种用于模型选择的信息准则，并从拟合优度项的角度，提出了一种新的准则：BICC。
The popular criteria in model selection are reviewed and a new criteria, BICC, which from the point of goodness-of-fit term, is suggested.
文献中已有的软件可靠性模型的选择方法和工具因为使用了受限的模型选择标准而得不到广泛的应用。
Tools and techniques in the literature can not be broadly used due to the limited number of model selection criteria they adopt.
文献中已有的软件可靠性模型的选择方法和工具因为使用了受限的模型选择标准而得不到广泛的应用。
Tools and techniques in the literature can not be broadly used due to the limited number of model selection criteria they adopt.
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