models.basemodel – Core TM interface

models.basemodel – Core TM interface

class gensim.models.basemodel.BaseTopicModel

Bases: object

get_topics()

Returns:num_topics x vocabulary_size array of floats which represents the term topic matrix learned during inference. Return type:np.ndarray

print_topic(topicno, topn=10)

Return a single topic as a formatted string. See show_topic() for parameters.

>>> lsimodel.print_topic(10, topn=5)
'-0.340 * "category" + 0.298 * "$M$" + 0.183 * "algebra" + -0.174 * "functor" + -0.168 * "operator"'

print_topics(num_topics=20, num_words=10)

Alias for show_topics() that prints the num_words most probable words for topics number of topics to log. Set topics=-1 to print all topics.