# Rule of thumb for k value in K nearest neighbor

I found that often used rule of thumb for k equals the square root of the number of points in the training data set in kNN.

In my problem I have 300 features of 1000 users and I use 10 fold cross validation.

Can someone tell me what value I should consider to obatin the square root? is it 300 or 1000?

• 1000 is the number of your points. You may want to understand the term curse of dimensionality before you start implementing. Once you understood the concept you may want to review your model and think about why this cannot work. – cel Nov 25 '15 at 7:53
• @cel Do you think kNN is not appropriate for my problem? :) – Volka Nov 25 '15 at 9:36