Given two classes of data on a plane:
(0,0), (0,2), (1,1), (2,0), (2,2) are in
the first class and
(0,1), (1,0), (1,2), (2,1) are in the second.
If you use the nearest neighbor method
to construct a model, how does the classifier look
like ? (i.e. how points on the whole
plane are assigned to different classes)
What is the training accuracy ?
If you use the k nearest neighbor method
with k=3 and assume all points are equally
important, what will the classifier look like ?
Then what is the training accuracy ?
Prove that different norms are equivalent
Using the unpaired t-test to explain why
in the following
competition
,
the approach RCO10310310 is not significantly more accurate.
Data are in the following zip
file if you find it's difficult to connect to the above
site.