(NMF) 在每次调用方法时，计算 NMF 中的一致性会生成不同的输出

如何解决(NMF) 在每次调用方法时，计算 NMF 中的一致性会生成不同的输出

我正在尝试计算每个主题的连贯性值，但每次运行代码时都会生成不同的值。

如果有人能回答这个问题会很有帮助。

提前致谢

def build_w2c(self,raw_documents):
    docgen = TokenGenerator(raw_documents,self.stop_words)
    new_list = []
    for each in docgen.documents:
        new_list.append(each.split(" "))
    # print(new_list)
    # Build the word2vec model
    self.w2v_model = gensim.models.Word2Vec(size=500,min_count=0.0005,sg=1)
    self.w2v_model.build_vocab(sentences=new_list)
    return self.w2v_model

def get_descriptor(self,all_terms,H,topic_index,top):
    # reverse sort the values to sort the indices
    top_indices = np.argsort(H[topic_index,:])[::-1]
    # Now get the terms corresponding to the top-ranked indices
    top_terms = []
    for term_index in top_indices[0:top]:
        top_terms.append(all_terms[term_index])
    return top_terms
def get_coherence(self,k,terms,H):
    k_values = []
    term_rankings = []
    coherences = []
    dict = {}
    for topic_index in range(1,k):
        print(topic_index)
        descriptor = self.get_descriptor(terms,10)
        term_rankings.append(descriptor)
    # Now calculate the coherence based on our Word2vec model
    #coherence = self.calculate_coherence(term_rankings)
        coherences.append(self.calculate_coherence(term_rankings))
        print("K=%02d: Coherence=%.4f" % (topic_index,coherences[-1]))
        k_values.append(topic_index)
        dict[topic_index] = coherences[-1]
    max_key = max(dict,key=dict.get)
    return k_values,coherences,max_key

def calculate_coherence(self,term_rankings):
    overall_coherence = 0.0
    for topic_index in range(len(term_rankings)):
        # check each pair of terms
        pair_scores = []
        for pair in combinations(term_rankings[topic_index],2):
            pair_scores.append(self.w2v_model.similarity(pair[0],pair[1]))
        # get the mean for all pairs in this topic
        topic_score = sum(pair_scores) / len(pair_scores)
        overall_coherence += topic_score
    # get the mean score across all topics
    return overall_coherence / len(term_rankings)

这是我在项目中使用的代码。

输出要求： 每次运行我的代码一致性应该是一样的。

如果你能帮我解决这个方法，那将是一个很大的帮助

非常感谢。