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[SOLVED] k-means doubt
Contributor II
k-means doubt
studying the performance of k-means, saw the traditional example
Medicine attribute_1 attribute_2
A 1 1
B 2 1
C 4 3
D 5 4
Where the two attributes are represented as points in the plane and the distance is calculated with the coordinates X and Y.
The question I have is how is the procedure when we have more than two attributes.
How do you represent and how to calculate the distance?.
If I'm working with 17,500 attributes.
there any other examples of k-means clustering with more than two attributes?
thanks
regards
studying the performance of k-means, saw the traditional example
Medicine attribute_1 attribute_2
A 1 1
B 2 1
C 4 3
D 5 4
Where the two attributes are represented as points in the plane and the distance is calculated with the coordinates X and Y.
The question I have is how is the procedure when we have more than two attributes.
How do you represent and how to calculate the distance?.
If I'm working with 17,500 attributes.
there any other examples of k-means clustering with more than two attributes?
thanks
regards
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Answers
k-Means uses a user-configurable distance measure. Some of the numerical measures are certainly known to you, like the Euclidean Distance. If you have questions about them, just post them here.
Best regards,
Marius