如何在vowpal wabbit中计算LDA模型的对数似然

本文介绍了如何在vowpal wabbit中计算LDA模型的对数似然的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我是典型的常规R用户.在 R 中有非常有用的 lda.collapsed.gibbs.sampler 在 lda 包tha使用折叠的Gibbs采样器来拟合潜在Dirichlet分配(LDA)模型，并使用Gibbs上一次迭代时的状态返回潜在参数的点估计采样.

I am typical, regular, everyday R user. In R there is very helpful lda.collapsed.gibbs.sampler in lda package tha uses a collapsed Gibbs sampler to fit a latent Dirichlet allocation (LDA) model and returns point estimates of the latent parameters using the state at the last iteration of Gibbs sampling.

此函数还有一个很棒的参数 compute.log.likelihood ，当设置为 TRUE 时，它将导致采样器计算日志每次扫描后，单词的可能性(在恒定因子之内)变量.这对于评估收敛性和比较不同的LDA模型(针对不同主题数进行计算)很有用.

This function also has a great parameter compute.log.likelihood which, when set to TRUE, will cause the sampler to compute the loglikelihood of the words (to within a constant factor) after each sweep over thevariables. This is useful for assessing convergence and in comparing different LDA models (computeted for different number of topics).

我对 vowpal_wabbit的LDA中是否有这样的选择感兴趣模型?

推荐答案

运行 vw -h --lda 1 时，帮助提供以下参数.默认情况下， metrics 参数处于关闭状态.它用于计算实现主题一致性的.尝试通过传递-metrics1

When running vw -h --lda 1 the help offers the following parameters.The metrics parameter is off by default.It is used to compute the topic coherence which is implemented here.Try to enable this functionality by passing --metrics 1

Latent Dirichlet Allocation:
  --lda arg                             Run lda with <int> topics

  --lda_alpha arg (=0.100000001)        Prior on sparsity of per-document topic
                                        weights
  --lda_rho arg (=0.100000001)          Prior on sparsity of topic
                                        distributions
  --lda_D arg (=10000)                  Number of documents
  --lda_epsilon arg (=0.00100000005)    Loop convergence threshold
  --minibatch arg (=1)                  Minibatch size, for LDA
  --math-mode arg (=0)                  Math mode: simd, accuracy, fast-approx
  --metrics arg (=0)                    Compute metrics

或直接跳转到 vw的源代码实用程序.

可以在此处找到有用的演示文稿，其中展示了大多数参数.

A helpful presentation showcasing most parameters can be found here.

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