how to find euclidean distance between one vector and many other vectors

Hi

I like to calculate Euclidean distance between my first matrix, which contains from one vector, and many other matrices which have similar dimensions ( row vectors ) and determine the smallest distance, and which matrix has it.

Example:

if I have D = [ 1 2 4]

and I1 = [3 5 5 ] , I2 = [ 5 7 8 ], I3 = [ 9 8 7 ] , I4 = [ 1 2 3 ]

so after calculating the Euclidean distance between D AND I1,I2,I3 and I4 the smallest distance will be between D and I4. D as reference

How can I do that????

Thank you

Answer 1

[Image Analyst]

Try pdist2() if you have the Statistics and Machine Learning Toolbox

D = [ 1 2 4]

I1 = [3 5 5 ]
I2 = [5 7 8 ]
I3 = [9 8 7 ]
I4 = [1 2 3 ]

IAll = [I1;I2;I3;I4]
distances = pdist2(D, IAll)
[minDistance, indexOfMinDistance] = min(distances)

You'll see:

D =

1 2 4

I1 =

3 5 5

I2 =

5 7 8

I3 =

9 8 7

I4 =

1 2 3

IAll =

3 5 5

5 7 8

9 8 7

1 2 3

distances =

3.74165738677394 7.54983443527075 10.4403065089106 1

minDistance =

1

indexOfMinDistance =

4

indexOfMinDistance will be 4, and since I put I4 into row 4, I4 has the closest distance to D.

[fathi]

Thanks a lot for this answer, clear.

[NISHANT GUPTA]

Hello Image Analyst you are a saviour i was initially thinking that i need to code this

I have data set of about 9000 points in 103 cell arrays and need to find this for each point in one array to another array and map the index for each point

Thanks

Answer 2

[KSSV]

doc pdist