What is the translation of " MODEL SELECTION " in Chinese?

• 模型选择

Examples of using Model selection in English and their translations into Chinese

Bayesian Model Selection.
贝叶斯模型选择）.

Model selection depends primarily on two aspects.
模式的选择主要从两个方面加以考虑。

AIC and BIC model selection criteria.
模型选择准则之AIC和BIC.

As before, we used the AIC for model selection.
与AIC相似，用于模型选择。

Potential users of LOO for model selection should weigh a few known caveats.
将LOO用于选择模型的潜在用户应该权衡一些已知的警告。

Similar to the AIC, it is also used for model selection.
与AIC相似，用于模型选择。

Let's talk about the specific model selection techniques for each system.
下面再来说说每个系统的具体机型选择技巧。

The process of selecting one method as the solution is called model selection.
选择一种方法作为解决方案的过程称为模型选择。

Section 3: Variables and model selection techniques.
第3部分：变量和模型选择技巧.

The following figure 3 shows the Predictive Maintenance Pipeline for Model Selection.
下面的图3显示了预测性维护的模型选择管道。

Potential users of LOO for model selection should weigh a few known caveats.
LOO用于模型选择的潜在用户应该重视一些已知的注意事项。

X adds the important feature of hyperparameter tuning, also known as model selection.
X增加了超参数调优的重要特性，也称为模型选择。

Chapter 6: Model selection, model specifications and various typologies of rapid estimates.
第6章：模型选择、模型确定和各种类型的快速估算.

Hitachi Elevator HsD Decoration Model Selection System".
日立电梯装饰选型系统自己心目当中.

Numerous model selection, professional construction team, senior technical guidance, dedicated to your service.
众多的机型选择,、专业的施工队伍、资深的技术指导，竭诚为您服务。

Computer automation of general-to-specific model selection procedures.
从一般到特殊模型选择过程的计算机自动化.

Model selection is the task of selecting a statistical model from a set of candidate models, given data.
模型选择是从给定数据的一组候选模型中选择统计模型的任务。

Information technology- Metamodel framework for interoperability(MFI)- Part 9: On demand model selection.
信息技术互操作性元模型框架(MFI)第9部分：按需模型选择.

Machine learning process steps like the model selection and the removal of Sensor Noises Using Auto-Encoders.
了解机器学习的处理步骤，如选择模型以及用Auto-Encoder技术去除传感器噪声.

I came to Tokyo in August 2010, and in September of the same year, I participated in the model selection of FLASH 2011.
年8月来到东京，同年9月，参与FLASH2011的模特选拔。

This step is called model selection: you selected a linear model of life satisfaction with just one attribute, GDP per capita(Equation 1-1).
这一步称为模型选择：选择一个生活满意度的线性模型，该模型只有一个属性（attribute），即人均GDP。

Researchers at Google have developed an approach to artificial intelligence(AI) model selection that achieves record speed and precision.
谷歌的研究人员已经开发出一种人工智能(AI)模型选择方法，以达到创纪录的速度和精度。

Most AutoML solutions address all parts of the ML pipeline, including data cleanup and hyper-parameter optimization as well as model selection.
大多数AutoML解决方案都处理ML管道的所有部分，包括数据清理、超参数优化和模型选择。

Cross validation iterators can also be used to directly perform model selection using Grid Search for the optimal hyperparameters of the model..
交叉验证迭代器也可用于使用GridSearch直接执行模型选择以获得模型的最佳超参数。

This step is called model selection: you selected a linear model of life satisfaction with just one attribute, GDP per capita(Equation 1-1).
这个过程称之为模型选择：你为生活满意度选择了一个线性模型，该模型只有一个属性，就是人均GDP（见以下公式）。

However, often difficult to deduce which part of the data is noise(cf. model selection, test set, minimum description length, Bayesian inference, etc.).
然而，常常很难判断那一部分数据是噪音（参见模型选择、测试集、最小描述长度、贝叶斯推断等等）。

As these models are incorporated more widely into critical business systems, it's important to consider explainability as a first-class model selection criterion.
由于这些模型被更广泛地合并到关键的业务系统中，因此将可解释性作为模型选择的头等标准非常重要。

The second part of the chapter will present model selection techniques, which will be particularly useful in identifying the best-fitting model and in discriminating among competing models..
本章第二部分将介绍模型选择技巧。这些技巧对于确定最恰当模型和区分相互竞争的模型特别有用。

The chapter will provide an overview of the subject treated in section 3, entitled" Variable and model selection techniques", together with a description of the structure of the chapters contained therein.
本章将提供对题为"变量和模型选择技巧"的第3部分所处理主题的一个概述，同时还要说明其中所含各章的结构。

While these models learn their parameters through data-driven methods, model selection(as architecture construction) through hyper-parameter choices remains a tedious and highly intuition driven task.
虽然这些模型通过数据驱动的方法学习参数，但通过超参数选择的模型选择（作为架构构造）仍然是单调乏味且高度直觉驱动的任务。