classification experiments with the k-Nearest Neighbor algorithm.

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Hi everyone
It's my first effort for KNN classification and am using wine data sample from UCI website. i was wondering what distance measures I can use in this case and how to get the computation time required to compute the distance from a sample to each other sample.
I want to determine its k nearest neighbors for each labeled sample, if the label of the sample is more common than any other label for the k nearest neighbors, then count the classification as correct. Otherwise, count the classification as incorrect.
I'd appreciate any input
Thanks
data set info: attributes :
1) Alcohol
2) Malic acid
3) Ash
4) Alcalinity of ash
and ... 13)xxx
it categorizes wines into 3 classes
one example would be:
1,14.23,1.71,2.43,15.6,127,2.8,3.06,.28,2.29,5.64,1.04,3.92,1065
  2 个评论
Walter Roberson
Walter Roberson 2013-2-5
Measuring computation time is difficult to do right, especially if what you are trying to do is predict how efficient different methods would be with larger datasets.
Husky
Husky 2013-2-5
Thanks walter, this dataset is small, only 178 lines each having 13 attributes

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回答(1 个)

Walter Roberson
Walter Roberson 2013-2-5
For timing, see the File Exchange Contribution timeit

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