Examples of using Generalized linear models in English and their translations into Chinese
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Generalized Linear Models.
广义线模型.Main and interaction effects were analyzed with generalized linear models.
Generalized linear models are provided by the GLM package.
广义线性模型由GLM包提供。Market research problems canalso be analyzed by using hierarchical generalized linear models.
市场问题也可以用分层广义线性模型来分析。Generalized Linear Models extend linear regression to:.
广义线性模型推导出线性回归：.Certain forms of nonlinear model can be fitted by Generalized Linear Models(glm()).
特定形式的非线性模型可以通过广义线性模型(glm())拟合。Generalized linear models extend the linear model in two ways.
广义线性模型通过两种方式对线性模型进行扩展。Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models.
解释概率模型：logit、probit以及其他广义线性模型.Generalized linear models are an extension of classic linear models. .
广义线性模型是经典线性模型的推广。Statistical Modelling: covers the main aspects of linear models and generalized linear models.
统计模型：包括线性模型和广义线性模型的主要方面。GEE models are an extension of Generalized Linear Models(GLM)(McCullagh and Nelder, 1989).
Generalized Linear Models, Tree-Based Models, and Neural Networks have all become fundamental aspects of the Machine Learning toolkit.
广义线性模型、基于树的模型和神经网络都已成为机器学习工具包中的基本元素。The statistical model specification is based on generalized linear models(McCullagh and Nelder 1989).
因此广义线性模型比一般线性模型有更广泛的应用(McCullagh&Nelder1989)。In hierarchical generalized linear models, the distributions of random effect u{\displaystyle u} do not necessarily follow normal distribution.
在分层广义线性模型中，随机效应的分布函数u{\displaystyleu}不必要满足正态分布。If the errors donot follow a multivariate normal distribution, generalized linear models may be used to relax assumptions about Y and U.
如果误差不遵循多元正态分布，则可以使用广义线性模型来放宽关于Y和U的假设。Besides supporting extensive deep learning with over 30 layer types, it supports standard models such as SVMs,tree ensembles, and generalized linear models.
除了支持30层以上的广泛深入学习，它还支持标准模型，如树集成、支持向量机(SVMs)和广义线性模型。One of the important contributions in statistical modelling is the concept of generalized linear models(Nelder and Wedderburn, 1972)17.
这种1-层映射是广义线性模型的例子（Nelder＆Wedderburn，1972）。Apart from that, extensive deep learning with over 30 layer types, it also supports standard models such as tree ensembles,SVMs, and generalized linear models.
除了支持30层以上的广泛深入学习，它还支持标准模型，如树集成、支持向量机(SVMs)和广义线性模型。These were mostly perceptrons andother models that were later found to be reinventions of the generalized linear models of statistics.
这些模型大多是感知器和其他模型，后来被发现是广义线性统计模型的再发明[12]。H2O supports the most widely used statistical& machine learningalgorithms including gradient boosted machines, generalized linear models, deep learning and more.
H2OAutoML支持最广泛使用的统计和机器学习算法，包括梯度增强机器、广义线性模型、深度学习等。GLIM(an acronym for Generalized Linear Interactive Modelling) is a statistical software program for fitting generalized linear models(GLMs).
The power of a generalized linear model is limited by its features.
广义线性模型的能力局限于其特征的性质。In this hierarchical generalized linear model, the fixed effect is described by β{\displaystyle\beta}, which is the same for all observations.
在分层广义线性模型中，固定效应为β{\displaystyle\beta}，对所有观测值都相同。Thus, you cannot fit a generalized linear model or multi-variate regression using this.
因此，你不能用它拟合一般的线性模型，或者是用它来进行多变量回归分析。Logistic regression can be seen as a kind of generalized linear model.
Logistic回归可以视作是广义线性回归模型的一种。Thus, you cannot fit a generalized linear model or multi-variate regression using this.
因此，你不能用广义线性模型或多变量回归来拟合。Not to be confused with Multiple linear regression, Generalized linear model or General linear methods.
不要与多元线性回归，广义线性模型或一般线性方法相混淆。There is no need toget confused with multiple linear regression, generalized linear model or general linear methods.
不要与多元线性回归，广义线性模型或一般线性方法相混淆。Logistic regression is a special case of a generalized linear model, and is more appropriate than a linear regression for these data, for two reasons.
逻辑回归是广义线性模型的特例，比线性回归更合适这些数据，原因有两个。
