I Have an object with a set of parameters like:
var obj = new {Param1 = 100; Param2 = 212; Param3 = 311; param4 = 11; Param5 = 290;}
On the other side i have a list of object:
var obj1 = new {Param1 = 1221 ; Param2 = 212 ; Param3 = 311 ; param4 = 11 ; Param5 = 290 ; }
var obj3 = new {Param1 = 35 ; Param2 = 11 ; Param3 = 319 ; param4 = 211 ; Param5 = 790 ; }
var obj4 = new {Param1 = 126 ; Param2 = 218 ; Param3 = 2 ; param4 = 6 ; Param5 = 190 ; }
var obj5 = new {Param1 = 213 ; Param2 = 121 ; Param3 = 61 ; param4 = 11 ; Param5 = 29 ; }
var obj7 = new {Param1 = 161 ; Param2 = 21 ; Param3 = 71 ; param4 = 51 ; Param5 = 232 ; }
var obj9 = new {Param1 = 891 ; Param2 = 58 ; Param3 = 311 ; param4 = 21 ; Param5 = 590 ; }
var obj11 = new {Param1 = 61 ; Param2 = 212 ; Param3 = 843 ; param4 = 89 ; Param5 = 210 ; }
What is the best (easiest) algorithm to find the closest match for the first obj in the listed objects?
You must define the term closest match before trying to find it!!
1- One way many people use is Mean Squared Error (or Euclidean Distance) :
Calculate mean square error for all objects:
Sqr(obj.Param1-obj1.Param1) + Sqr(obj.Param2-obj1.Param2) + ..... // for obj1
Sqr(obj.Param1-obj2.Param1) + Sqr(obj.Param2-obj2.Param2) + ..... // for obj2
and choose the one with the minimum value...
2- You may also use Minimum absolute error :
Abs(obj.Param1-obj1.Param1) + Abs(obj.Param2-obj1.Param2) + ..... // for obj1
Abs(obj.Param1-obj2.Param1) + Abs(obj.Param2-obj2.Param2) + ..... // for obj2
and choose the one with the minimum value...
3- Also you can apply k-nearest neighbour with any criteria you have chosen above
It all depends on the properties of these parameters...
For more reading you may look at List of Classification algorithms
Depends, i guess. Several possibilities come to my mind:
- SAD: calculate the absolute difference of each pair of parameters (the one you test and each of your candidates) and sum them up. Lowest number is closest
- L2-Norm: Calculate the difference of each pair of parameters, square them, sum them up, take square root
- Cosine: Multiply each parameter with the other parameter, sum up. Divide result by product of length (L2-Norm) of both objects
of course, there are thousand more possibilities, therefore you have to specify, what you want exactly!
You could also use the Euclidean Distance.
Essentially you pretend each object is a point in 5 dimensions and look for the point that's closest (i.e.: has the shortest distance).
来源：https://stackoverflow.com/questions/3007790/finding-the-closest-match