Understanding the impact of 'k'
There is a complex relationship between k and classification accuracy. Bigger is not always better.
Which of these is a valid reason for keeping k as small as possible (but no smaller)?
This exercise is part of the course
Supervised Learning in R: Classification
Hands-on interactive exercise
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