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R语言 topicmodels包 TopicModelcontrol-class()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 11:04:10 | 显示全部楼层 |阅读模式
TopicModelcontrol-class(topicmodels)
TopicModelcontrol-class()所属R语言包:topicmodels

                                        Different classes for controlling the estimation of topic models
                                         不同类别的控制主题模型的估计

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Classes to control the estimation of topic models which are inheriting from the virtual base class "TopicModelcontrol".
估计的主题模式,继承虚基类"TopicModelcontrol"类控制。


类对象----------Objects from the Class----------

Objects can be created from named lists.
可以创建对象的命名列表。


插槽----------Slots----------

Class "TopicModelcontrol" contains
类"TopicModelcontrol"包含




seed: Object of class "integer"; used to set
seed:类的对象"integer";用于设置




verbose: Object of class "integer". If a positive integer, then the progress is reported every verbose iterations. If 0 (default), no output is generated
verbose:对象的类"integer"。如果一个正整数,那么进度报告每verbose迭代。如果为0(默认),不生成输出




save: Object of class "integer". If a positive integer the estimated model is saved all verbose iterations. If 0 (default), no output is generated during model
save:对象的类"integer"。如果一个正整数估计模型保存所有verbose迭代。如果为0(默认),没有输出过程中产生的模型




prefix: Object of class "character"; path
prefix:对象的类"character";路径




nstart: Object of class "integer". Number of
nstart:对象的类"integer"。数




best: Object of class "logical"; if TRUE only the model with the maximum (posterior) likelihood is returned,
best:类的对象"logical"如果TRUE只有模型的最大(后)的可能性则返回,




keep: Object of class "integer"; if a positive
keep:积极的类的对象"integer";




estimate.beta: Object of class "logical"; controls if beta, the term distribution of the topics, is fixed,
estimate.beta:类"logical";控制的对象,如果公测,术语经销的主题,是固定的,

Class "VEMcontrol" contains
类"VEMcontrol"包含




var: Object of class "OPTcontrol"; controls the variational inference for a single document, by default
var:类的对象"OPTcontrol";控制的变化推断为一个单一的文件,默认情况下,




em: Object of class "OPTcontrol"; controls the variational EM algorithm, by default iter.max equals 1000
em:类的对象"OPTcontrol";控制的变分EM算法,的默认iter.max等于1000




initialize: Object of class "character"; one of "random", "seeded" and "model", by default
initialize:类的对象"character"; "random","seeded"和"model",默认情况下,

Class "LDAcontrol" extends class "TopicModelcontrol" and has the additional slots
类"LDAcontrol"类"TopicModelcontrol"延伸,并有额外的插槽




alpha: Object of class "numeric"; initial
alpha:对象类"numeric"初始

Class "LDA_VEMcontrol" extends classes "LDAcontrol" and "VEMcontrol" and has the additional slots
类"LDA_VEMcontrol"类"LDAcontrol"和"VEMcontrol"延伸,并有额外的插槽




estimate.alpha: Object of class "logical"; indicates if the parameter alpha is fixed a-priori or estimated, by
estimate.alpha:类的对象"logical";表示如果参数α是固定的,先验的或估计,

Class "LDA_Gibbscontrol" extends classes "LDAcontrol" and has the additional slots
类"LDA_Gibbscontrol"类"LDAcontrol"延伸,并有额外的插槽




delta: Object of class "numeric"; initial value
delta:类的对象"numeric"初始值




iter: Object of class "integer"; number of
iter:对象类"integer"数量的




thin: Object of class "integer"; number of
thin:对象类"integer"数量的




burnin: Object of class "integer"; number of
burnin:对象类"integer"数量的

Class "CTM_VEMcontrol" extends classes "TopicModelcontrol" and "VEMcontrol" and has the additional slots
类"CTM_VEMcontrol"类"TopicModelcontrol"和"VEMcontrol"延伸,并有额外的插槽




cg: Object of class "OPTcontrol"; controls the conjugate gradient iterations in fitting the variational mean and variance per document, by default iter.max equals 500 and
cg类的对象"OPTcontrol";在装修变的均值和方差的每个文档,默认情况下,iter.max控制的共轭梯度迭代等于500

Class "OPTcontrol" contains
类"OPTcontrol"包含




iter.max: Object of class "integer"; maximum
iter.max:对象类"integer",最大




tol: Object of class "numeric"; tolerance for
tol:对象类"numeric";容忍


(作者)----------Author(s)----------


Bettina Gruen

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
注2:由于是机器人自动翻译,难免有不准确之处,使用时仔细对照中、英文内容进行反复理解,可以帮助R语言的学习。
注3:如遇到不准确之处,请在本贴的后面进行回帖,我们会逐渐进行修订。
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