text-mining - gensim 的 get_document_topics 方法返回的概率不等于 1

Question

有时它返回所有主题的概率，一切都很好，但有时它只返回几个主题的概率，它们加起来不等于一个，这似乎取决于文档。一般来说，当它返回的主题很少时，概率加起来或多或少 80%，那么它是否只返回最相关的主题？有没有办法强制它返回所有概率？

也许我遗漏了一些东西，但我找不到该方法参数的任何文档。

Answer 1

我遇到了同样的问题并通过包含参数 minimum_probability=0 解决了它调用 get_document_topics 时gensim.models.ldamodel.LdaModel的方法对象。

    topic_assignments = lda.get_document_topics(corpus,minimum_probability=0)

默认情况下， gensim 不输出低于 0.01 的概率，因此，特别是对于任何文档，如果有任何主题分配的概率低于此阈值，则该文档的主题概率之和不会加起来为 1。

这是一个例子:

from gensim.test.utils import common_texts
from gensim.corpora.dictionary import Dictionary
from gensim.models.ldamodel import LdaModel

# Create a corpus from a list of texts
common_dictionary = Dictionary(common_texts)
common_corpus = [common_dictionary.doc2bow(text) for text in common_texts]

# Train the model on the corpus.
lda = LdaModel(common_corpus, num_topics=100)

# Try values of minimum_probability argument of None (default) and 0
for minimum_probability in (None, 0):
    # Get topic probabilites for each document
    topic_assignments = lda.get_document_topics(common_corpus,minimum_probability=minimum_probability)
    probabilities = [ [entry[1] for entry in doc] for doc in topic_assignments ]
    # Print output
    print(f"Calculating topic probabilities with minimum_probability argument = {str(minimum_probability)}")
    print(f"Sum of probabilites:")
    for i, P in enumerate(probabilities):
        sum_P = sum(P)
        print(f"\tdoc {i} = {sum_P}")

输出将是:

Calculating topic probabilities with minimum_probability argument = None
Sum of probabilities:
    doc 0 = 0.6733324527740479
    doc 1 = 0.8585712909698486
    doc 2 = 0.7549994885921478
    doc 3 = 0.8019999265670776
    doc 4 = 0.7524996995925903
    doc 5 = 0
    doc 6 = 0
    doc 7 = 0
    doc 8 = 0.5049992203712463
Calculating topic probabilities with minimum_probability argument = 0
Sum of probabilites:
    doc 0 = 1.0000000400468707
    doc 1 = 1.0000000337604433
    doc 2 = 1.0000000079162419
    doc 3 = 1.0000000284053385
    doc 4 = 0.9999999937135726
    doc 5 = 0.9999999776482582
    doc 6 = 0.9999999776482582
    doc 7 = 0.9999999776482582
    doc 8 = 0.9999999930150807

此默认行为在文档中没有很清楚地说明。 minimum_probability 的默认值对于 get_document_topics方法是 None ，但是这不会将概率设置为零。而是 minimum_probability 的值设置为 minimum_probability 的值的 gensim.models.ldamodel.LdaModel对象，默认为 0.01，如 source code 中所示:

def __init__(self, corpus=None, num_topics=100, id2word=None,
             distributed=False, chunksize=2000, passes=1, update_every=1,
             alpha='symmetric', eta=None, decay=0.5, offset=1.0, eval_every=10,
             iterations=50, gamma_threshold=0.001, minimum_probability=0.01,
             random_state=None, ns_conf=None, minimum_phi_value=0.01,
             per_word_topics=False, callbacks=None, dtype=np.float32):