Why does cosine similarity work better than Euclidean distance?
Updated May 15, 2026
Short answer
It measures angle instead of magnitude.
Deep explanation
Cosine similarity is less affected by magnitude scaling and works better in sparse high-dimensional spaces.
Real-world example
Text similarity in NLP embeddings.
Common mistakes
- Using Euclidean distance for sparse vectors.
Follow-up questions
- When does cosine fail?
- Is it scale invariant?