When dealing with high-dimensional data, which of the two algorithms (k-NN or Naive Bayes) is likely to be more efficient in terms of computational time?
- Both Equally Efficient
- Naive Bayes
- Neither is Efficient
- k-NN
Naive Bayes is typically more efficient in high-dimensional data due to its simple probabilistic calculations, while k-NN can suffer from the "curse of dimensionality."
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