clustering algorithms

Definition of distance between data:

 (1) Hamming Distance: d(i,j)=sum(abs(x(i,k)-x(j,k))) | k from 1 to m

 (2) Euclid Distance: d(i,j)=sum((x(i,k)-x(j,k))^2)  | k from 1 to m

 (3) Mahalanobis Distance: Eliminiate the units of each vector.

Non-distance methods:

 (1)

To be continued...

原文地址:https://www.cnblogs.com/jast/p/4485866.html