Making a group of maximum nearest elements.

%for row vectors:
%example data
A = [1,4,2,6,9,0,4.2,5.6];
B = [0.1,4.1,3];
assert(isrow(A) && isrow(B), 'Inputs must be row vectors');
[~, groupA] = min(abs(A - B.'), [], 1)
%for column vectors:
%demo data
A = A.'; B = B.';
assert(iscolumn(A) && iscolumn(B), 'Inputs must be column vectors')
[~, groupA] = min(abs(A.' - B), [], 1)

I'm not sure how this should be applied to your example datasheet. Looking at what it contains, you should import that excel file in a table, in which case you should store the group as another variable of the table so you can then use aggregation functions such as groupsummary.

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BHAGYALAKSHMI M 2020-3-12

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Thank you sir.

I am not getting the output,there was some errors.

The following is my points.

B=
Columns 1 through 10
8481    1.7293    1.4514    0.6036  199.6823   29.9475   35.4337    6.5257    3.2450    0.9861
3333    1.8333    1.6500    0.6500  492.5000   26.8333   32.1667    6.5333    2.6167    0.6617
4286    1.7143    2.0714    0.9286  198.0000   53.1429   93.4286    5.8000    2.9000    1.0114
0000    2.0000    9.0250    4.5750  207.0000   62.2500  181.2500    6.7500    2.7000    1.1750
0000    2.0000    1.4000    0.7000  470.0000   62.0000   88.0000    5.6000    2.5000    0.8000
3333    2.0000    3.4333    1.4667  287.3333   67.3333  139.3333    5.6000    2.4667    0.7667
0000    1.3333    0.8333    0.1667  392.0000   25.0000   66.3333    7.0667    3.5667    1.0667
0000    2.0000    0.7000    0.1000  392.0000   20.0000   30.0000    5.3000    2.8000    1.1000
0000    1.0000   22.6000   11.4000  558.0000   30.0000   37.0000    7.8000    3.4000    0.8000
0000    2.0000    3.7000    2.1000  490.0000  115.0000   91.0000    6.5000    2.8000    0.7000
0000    2.0000    2.7000    1.2000  365.0000   62.0000   55.0000    6.0000    2.4000    0.6000
3333    2.0000    5.1000    2.2000  223.3333   60.3333  149.0000    6.9000    2.8333    0.6333
  Column 11
3867
5000
2857
0000
0000
0000
0000
0000
0000
0000
0000
0000

How can I find nearest points of this from my dataset? Please help me.

BHAGYALAKSHMI M 2020-3-14

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If I take the unique values, then I get some B like--

Choosing this as B how can I find all neighbors of these points.

A is a data, B is some points suppose B contains 50 points then we will get 50 groups. Suppose the data contains some points like: {1,0.3,4,7,9,23,55, etc} (a matrix). B contains:{ 0.4,10,44,60,etc}.

Check the whole data, the first point is '1' in the data. This point is close to 0.4 compared to the other points in B. Next is 0.3, this also close to 0.4 compared to others. So we got a group like 0.4,0.3,1. This process continues when all the elements in the data checked. At last, we get some groups/clusters. Like

C1=[1,0.4,0.3,4]

Then 7 (from data) that is close to 10 then

C2=[7,10,9,23]

55 close to 60 compared to others

C3=[55,60]

The 44 is remaing, this is close to C3 elements so

C3=[44,55,60].

How can get some groups that contains(the groups) all the elements inthe dataset ?

Please help me.

BHAGYALAKSHMI M 2020-3-17

I want to take each group elements. Like:

group(1)=[elements]

group(2)=[elements] etc.

How can I get this?

Guillaume 2020-3-17

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As I've said, this is typically a bad idea. I was asking about what you want to do after that. It is very likely that whatever it is, it will be much easier if you don't do this.

Now if you really insist:

group = accumarray(a(:), groupnumber(:), [], @(v) {v});

or

group = splitapply(@(v) {v}, a(:), groupnumber(:));

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