Comments (11)
You can output them in order with the following code:
the topic list: print llda_model.topics
the term(word) list: print llda_model.terms
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aaa i see2 thankyouu again!!
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Halo Joe, I really confused with the result, why the beta (topic-word)
result same number (probability) for every label (my label is rating
1,2,3,4,5). Do you know why? Should I increase the iteration number? Really
appreciate your answer because this is for my undergraduate thesis.
Thankyouu
fyi : differensial is (5+4) - (1+2)
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How many iterations did you use? may be you can try more iterations.
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I use 1000 iteration
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Probably because you have too little data.
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aaah i see2 maybe thats the reason. Also I want to ask which one better I use to train a model? the (1) or (2)?
Training
(1) --> #llda_model.training(iteration=100, log=True)
(2) --> #while True:
print("iteration %s sampling..." % (llda_model.iteration + 1))
llda_model.training(1)
print("after iteration: %s, perplexity: %s" % (llda_model.iteration, llda_model.perplexity()))
print("delta beta: %s" % llda_model.delta_beta)
if llda_model.is_convergent(method="beta", delta=0.01):
break
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Both of them will be ok. If you do not know how many iterations it takes for the model to converge, you can use (2) to get a convergent model.
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Aaaah I see2 , okee Joe thankyouu so much for all the answer😊
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Happy to help!
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