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Let's say you take as density a number around which there are other numbers at a distance of no more than 8.
the delta would be 8
Take number 13, it has deltas associated with the numbers.
delta 3 is the number 10
2 - 15
8 - 21.
we get a series of 10, 13, 15, 21...
you do this with each number, then you remove the groups with repeating numbers and leave the highest densities
I don't know what you did, it has nothing to do with the algorithm at all, I'll try to rephrase
Yes, I didn't take into account that the area is expanding, then I got the following table
If you add a grade 6 (delta with a value of 6), you get the following table
As you can see, the number 71 and 65 appeared compared to my algorithm because the delta between 65 and 71 is 6.
If you add a grade 6 (delta with a value of 6), you get the following table
As you can see, the number 71 has appeared compared to my algorithm because the delta between 65 and 71 is 6.
The bottom line is this. If you need to find the points with the highest density, do as you did a couple of pages ago.
So far the bottom line is that there is no complete algorithm.
The largest density is the abstraction - there we found the numbers that are closest to all the other numbers.
Clusters we could not divide into groups - to classify - I understand that we need to go through all classes, and determine the density of each group, then compare the density.
About the area on a straight line - I'm not sure...
In general, am I understanding you correctly?