感谢您的光临。我试图为这张显示为空白的图表寻求一些帮助。我正在关注本教程#17 https://www.machinelearningplus.com/nlp/topic-modeling-gensim-python/使用 LDAMallet 构建不同数量主题的连贯性分数图表。这是我的代码:
os.environ['MALLET_HOME'] = 'C:\\mallet\\mallet-2.0.8'
mallet_path = 'C:\\mallet\\mallet-2.0.8\\bin\\mallet'
dictionary = gensim.corpora.Dictionary(processed_docs[:])
bow_corpus = [dictionary.doc2bow(doc) for doc in processed_docs]
def compute_coherence_values(dictionary, bow_corpus, documents, limit, start=2, step=3):
"""
Compute c_v coherence for various number of topics
Parameters:
----------
dictionary : Premium Billing data
corpus : Gensim bow_corpus
texts : document
limit : Max num of topics
Returns:
-------
model_list : List of LDA topic models
coherence_values : Coherence values corresponding to the LDA model with respective number of topics
"""
coherence_values = []
model_list = []
for num_topics in range(start, limit, step):
model = gensim.models.wrappers.LdaMallet(mallet_path, corpus=bow_corpus, num_topics=num_topics, id2word=dictionary)
model_list.append(model)
coherencemodel = CoherenceModel(model=model, texts=documents, dictionary=dictionary, coherence='c_v')
coherence_values.append(coherencemodel.get_coherence())
return model_list, coherence_values
# Can take a long time to run.
model_list, coherence_values = compute_coherence_values(dictionary=dictionary, bow_corpus=bow_corpus,
documents=documents, start=2, limit=40, step=6)
# Show graph
limit=40; start=2; step=6;
x = range(start, limit, step)
plt.plot(x, coherence_values)
plt.xlabel("Num Topics")
plt.ylabel("Coherence score")
plt.legend(("coherence_values"), loc='best')
plt.show() 
# Print the coherence scores
for m, cv in zip(x, coherence_values):
print("Num Topics =", m, " has Coherence Value of", round(cv, 4)) 
数据:
我希望它看起来像什么:
请帮忙
最佳答案
我认为问题在于函数 CoherenceModel 中参数“texts”的赋值。我不确定您如何定义传递的值“文档”，但我使用了以下内容:
coherence_model_lda = CoherenceModel(model=lda_model, texts=[tokens], dictionary=dict, coherence='c_v')
我将“标记”定义为单词列表。如果我传递了 texts = tokens，它给了我 nan，然后当我将它传递到上面的列表中时，它工作正常!
关于python - 相干图空白 - nan 的相干值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/55816686/