从lda gensim检索topic-word数组和document-topic数组

Question

Situation:

I have a numpy term-document matrix example: [[0,1,0,0....],....[......0,0,0,0]].

I have plugged in the above matrix to the ldamodel method of the gensim. And it is working fine with the lad method lda = LdaModel(corpus, num_topics=10) . corpus is my term-document matrix mentioned above. I needed two intermediate matrices( topic-word array & document-topic array ) for research purpose.

1) per document-topic probability matrix (p_d_t)

2) per topic-word probability matrix (p_w_t)

Question:

How to get those array from the gensim LdaModel() function.? Kindly help me with getting those matrices.

Answer 1

1.Per-document topic probability matrix:

Apply a transformation to your corpus.

docTopicProbMat = lda[corpus]

2. Per-topic word probability matrix:

K = lda.num_topics topicWordProbMat = lda.print_topics(K)