相关疑难解决方法(0)

这里，best_model_lda 是一个基于 sklearn 的 LDA 模型，我们正在尝试找到该模型的一致性分数。

coherence_model_lda = CoherenceModel(model = best_lda_model,texts=data_vectorized, dictionary=dictionary,coherence='c_v')
coherence_lda = coherence_model_lda.get_coherence()
print('\n Coherence Score :',coherence_lda)

输出：出现此错误是因为我正在尝试查找 sklearn LDA 主题模型的连贯性分数，有没有办法解决它。另外，sklearn LDA 使用什么指标将这些单词分组在一起？

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AttributeError                            Traceback (most recent call last)
~\AppData\Local\Continuum\anaconda3\lib\site-packages\gensim\models\coherencemodel.py in _get_topics_from_model(model, topn)
   490                 matutils.argsort(topic, topn=topn, reverse=True) for topic in
--> 491                 model.get_topics()
   492             ]

AttributeError: 'LatentDirichletAllocation' object has no attribute 'get_topics'

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-106-ce8558d82330> in <module>
----> 1 coherence_model_lda = CoherenceModel(model = best_lda_model,texts=data_vectorized, …