Get coherence score for PLSA
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- Dominant language
- Python
- Stars
- 113
- Forks
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Description
PLSA and other methods gives strange coherence score:
```
PLSA(n_components=3).fit(data_vec).coherence()
PLSA(n_components=4).fit(data_vec).coherence()
```
```
n=5, -894.0931521853117
n=4, -846.5056881515624
n=1000, -548.1772075123278
```
When I use gensim, I get quite a good score:
```
2 & 0.4492
3 & 0.4257
4 & 0.4308
5 & 0.4443
6 & 0.4625
7 & 0.455
8 & 0.4791
9 & 0.4897
10 & 0.5354
11 & 0.5165
12 & 0.5149
13 & 0.5382
14 & 0.5546
15 & 0.5669
16 & 0.5633
17 & 0.5323
```
Could you please tell whether there is a bug?
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the PLSA coherence() calls shown in the issue and compare their outputs with the reported gensim scores. Trace the coherence implementation and determine whether the discrepancy is an implementation bug; done means identifying the cause and adding a regression test for the corrected behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100