Question

Implement a simple loop that trains an NMF topic model, for number of topics from 2 to 10 inclusive. At each iteration, compute your topic coherence measure on the top 10 words for each topic. Then compute the median topic coherence over all these topic scores. Your function should return a list of 9 median coherence scores, corresponding to each choice of the number of topics to use with N MF.

Name: implement a simple loop that trains an nmf topic model for number of topics from 2 to 10 inclusive at each iteration compute your topic coherence measure on the top 10 words for each topic t 71393
Uploaded: 2023-11-21T03:28:33-08:00
Duration: 5 min 9 s
Channel: Supreeta N
Description: implement a simple loop that trains an nmf topic model for number of topics from 2 to 10 inclusive at each iteration compute your topic coherence measure on the top 10 words for each topic t 71393

          Implement a simple loop that trains an NMF topic model, for number of topics from 2 to 10 inclusive. At each iteration, compute your topic coherence measure on the top 10 words for each topic. Then compute the median topic coherence over all these topic scores.
Your function should return a list of 9 median coherence scores, corresponding to each choice of the number of topics to use with N
MF.

Added by Lauren S.

Computer Science and Information Technology

Trishna Knowledge Systems 2018 Edition

Instant Answer

Solved by Expert Supreeta N

11/21/2023

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Implement a simple loop that trains an NMF topic model, for number of topics from 2 to 10 inclusive. At each iteration, compute your topic coherence measure on the top 10 words for each topic. Then compute the median topic coherence over all these topic scores. Your function should return a list of 9 median coherence scores, corresponding to each choice of the number of topics to use with N MF.