NLP - Word Embeddings
You run t-SNE on word embeddings but get a ValueError: "perplexity must be less than n_samples". What is the likely cause and fix?
You run t-SNE on word embeddings but get a ValueError: "perplexity must be less than n_samples". What is the likely cause and fix?
medium📝 Debug Q14 of 15
Step-by-Step Solution
Solution:
Step 1: Understand perplexity parameter in t-SNE
Perplexity controls neighborhood size and must be less than the number of samples.Step 2: Identify cause of ValueError
Error means perplexity is set equal or larger than sample count, which is invalid.Step 3: Fix by lowering perplexity
Reduce perplexity to a value smaller than the number of samples to fix the error.Final Answer:
Perplexity is set too high; reduce it below the number of samples -> Option BQuick Check:
Perplexity < n_samples to avoid error [OK]
Quick Trick: Keep perplexity less than sample count in t-SNE [OK]
Common Mistakes:
MISTAKES- Changing input shape instead of perplexity
- Ignoring the perplexity limit
- Assuming normalization fixes this error
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