Bird
0
0

After training an LDA model, you notice topics are very similar and not distinct. What is a likely fix?

medium📝 Debug Q7 of 15
NLP - Topic Modeling
After training an LDA model, you notice topics are very similar and not distinct. What is a likely fix?
AIncrease the number of topics
BRemove stopwords from the corpus
CDecrease the number of passes
DUse a smaller dictionary
Step-by-Step Solution
Solution:

  1. Step 1: Understand cause of similar topics

    Common words (stopwords) can cause topics to overlap and be less distinct.

  2. Step 2: Apply preprocessing fix

    Removing stopwords cleans the corpus and helps LDA find clearer topics.

  3. Final Answer:

    Remove stopwords from the corpus -> Option B

  4. Quick Check:

    Stopwords removal improves topic distinctness [OK]
Quick Trick: Clean text by removing stopwords for better topics [OK]
Common Mistakes:
MISTAKES
  • Only increasing topics without cleaning data
  • Reducing passes which may reduce training quality
  • Shrinking dictionary without cleaning

Want More Practice?

15+ quiz questions · All difficulty levels · Free

Free Signup - Practice All Questions
More NLP Quizzes
Sentiment Analysis Advanced - Domain-specific sentiment - Quiz 9hard Sentiment Analysis Advanced - Sentiment with context (sarcasm, negation) - Quiz 9hard Sequence Models for NLP - Attention mechanism basics - Quiz 4medium Text Generation - Language modeling concept - Quiz 6medium Text Generation - N-gram language models - Quiz 3easy Text Generation - Beam search decoding - Quiz 2easy Text Generation - Evaluating generated text (BLEU, ROUGE) - Quiz 1easy Word Embeddings - Visualizing embeddings (t-SNE) - Quiz 9hard Word Embeddings - FastText embeddings - Quiz 13medium Word Embeddings - Word similarity and analogies - Quiz 10hard