Question

I want to differentiate data vectors to find those that are similar. For example:

A=[4,5,6,7,8];
B=[4,5,6,6,8];
C=[4,5,6,7,7];

D=[1,2,3,9,9];
E=[1,2,3,9,8];

In the previous example I want to distinguish that A,B,C vectors are similar (not the same) to each other and D,E are similiar to each other. The result should be something like: A,B,C are similar and D,E are similar, but the group A,B,C is not similar to the group of D,E. Matlab can do this?
I was thinking using some classification algorithm or Kmeans,ROC,etc.. but I’m not sure which one will be the best one.

Any suggestion? Thanks in advance

Answer 1

Here it goes the solution I propose based on your results:

Z = [A;B;C;D;E];
Y = pdist(Z);
matrix = SQUAREFORM(Y);
matrix_round = round(matrix);

Now that we have the vector we can set the threshold based on the maximun value and decide with which theshold is the most appropriate.

It would be nice to create some cluster plot showing the differences between them.

Best regards