Aggregation Functions: Easy to Characterise?

In summary, the conversation discusses the characterization of aggregation functions, specifically those that are commutative and associative like addition, multiplication, maximum, minimum, and count. Other classes of such functions are mentioned, as well as the possibility of mapping them onto addition. The concept of equivalence classes for aggregate functions is also brought up, with examples of functions that are not equivalent to addition. The conversation ends with a question about the function "count" and how it can also be mapped onto addition.
  • #1
Gerenuk
1,034
5
Is the set of aggregation functions easy to characterise? I mean functions like addition, multiplication, maximum, minimum, count...
So basically everything that's commutative and associative:
[tex]
f(x,y)=f(y,x)
[/tex]
[tex]
f(f(x,y),z)=f(x,f(y,z))
[/tex]

What are other classes of such functions?
I can't all map to just addition, can I? I'd have no idea how to do it with the max(x,y) function?!
 
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  • #2
Every function on the set of n-element subsets of X is an aggregation function on X^n in the obvious way, right? Which would imply there's too many of them to characterize easily.
edit: oops, I forgot about associativity.
 
  • #3
I'm not sure what this means. Can you say it with an example?

(Of course all functions that somehow map to normal addition are one class only.)
 
  • #4
I noticed that even the max function maps onto addition by
[tex]max(x,y)=\lim_{p\to\infty}\sqrt[p]{x^p+y^p}[/tex]
Are there aggregate functions that do not map to addition?
 
  • #5
What about something like f(x, y) = x - y? This is not commutative. The function could be thought of as the signed distance between two numbers on the real line.
 
  • #6
But it is not associative nor commutative. So not an aggregate function I'm considering.
 
  • #7
OK.
How about something like
[tex]\prod_{i = 1}^n a_i[/tex]
?
That doesn't map to addition, and it's commutative and associative.
 
  • #8
Hmm? You mean multiplication?
It easily maps to addition through logarithms.
 
  • #9
could you be more precise with what you mean by 'maps to addition'?
 
  • #10
Instead of multiplying, I only need to "translate" the variables by logarithms and then the "structure" is the same as addition.
[tex]b_i=\ln a_i[/tex]
[tex]b_\text{tot}=\sum_{i=1}^n b_i[/tex]
I'm not sure what the mathematical terms are, but with this view all two value functions f(x,y) which can be created with an arbitrary one value function g(x) are "one class" and uninteresting.
[tex]f(x,y)=g^{-1}(g(x)+g(y))[/tex]
Because its obviously easy to use this procedure to generate more aggregate functions.
 
  • #11
I see, so 2 aggregate functions f(x,y) and g(x,y) are equivalent if there exists a 'translation' t such that

[tex]f(x,y)= t^{-1} \circ g( tx, ty) [/tex]

product is equivalent to addition by setting t=log
max is equivalent to addition by setting [tex]t: x \mapsto x^\infty[/tex]
etc


and we are trying to classify these equivalence classes of aggregate functions.


One aggregation that isn't equivalent to addition is the constant function. Also all the constant functions are in the same class (take t to be any map that takes c to d, then c=t^-1 d).



btw, what is 'count' (your last example in the first post) ?
 
  • #12
Maybe I shouldn't require for [itex]g^{-1}[/itex] to exist. So it doesn't have to be 1-to-1.
Then the constant function and also COUNT also somehow map onto addition?
I could map constants to infinity. And for COUNT I map all values to 1 and then add.

COUNT counts the number of variables. So
Count(a1,a2,...,aN)=N
 

FAQ: Aggregation Functions: Easy to Characterise?

1. What are aggregation functions?

Aggregation functions are mathematical functions that combine multiple values into a single output value. They are commonly used in data analysis and decision-making to summarize and interpret large sets of data.

2. How are aggregation functions characterized?

Aggregation functions are characterized by their properties, which describe how they behave when applied to different sets of data. These properties include monotonicity, continuity, and idempotence, among others.

3. Why are aggregation functions easy to characterize?

Aggregation functions are easy to characterize because they have well-defined and consistent properties that can be mathematically proven. This makes it easier to compare different aggregation functions and understand their behavior.

4. What is the importance of characterizing aggregation functions?

Characterizing aggregation functions is important because it allows for a better understanding of how they work and how they can be used in different contexts. It also helps in choosing the most appropriate aggregation function for a specific problem or dataset.

5. Can aggregation functions be combined?

Yes, aggregation functions can be combined or composed to create more complex functions. This allows for more flexibility in data analysis and decision-making, as different combinations can be used to achieve different results or meet specific requirements.

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