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So I recently came along kNN k nearest neighbour. When looking at its disadvantages, most of the literature mentions it is costly, lazy, requires full training data plus depends on the value of k and has the issue of dimensionality because of the distance. Other than that I have following hypothesis.

1- It ignores the fact that dimensions can be inter related and instead assumes they are independent (as we are just calculating distance) 2- Has the issue of normalization of data... if the data is not normalized distance can be biased towards a specific dimension

I will like to have a comprehensive analysis on the disadvantages of kNN apart from those mentioned above and if they are wrong then why.

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  1. It doesn't handle categorical variables very well
  2. It doesn't handle 'soft' boundaries - i.e. areas where some cases appear on either side of a boundary. See also mathbabe here: https://mathbabe.org/?s=nearest+neighbor - for extended criticism.
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