寻找最接近的匹配
我有一个带有一组参数的对象，例如：
var obj = new {Param1 = 100; Param2 = 212; Param3 = 311; param4 = 11; Param5 = 290;}
在另一边，我有一个对象列表：
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 ; }
在列出的对象中找到第一个 obj 最接近的匹配的最佳（最简单）算法是什么？
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?
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在尝试查找之前，您必须定义术语最接近的匹配！
1-许多人使用的一种方法是均方误差（或欧几里得距离) :
计算所有对象的均方误差：
并选择具有最小值的一个...
2-您还可以使用最小绝对误差：
并选择最小值...
3-您还可以根据您拥有的任何条件应用k-最近邻上面选择的
这一切都取决于这些参数的属性...
有关更多阅读，您可以查看 分类列表算法
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:
and choose the one with the minimum value...
2- You may also use Minimum absolute error :
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
我想，要看情况。我想到了几种可能性：
当然，还有数千种可能性，因此您必须指定您到底想要什么！
Depends, i guess. Several possibilities come to my mind:
of course, there are thousand more possibilities, therefore you have to specify, what you want exactly!
您还可以使用欧几里得距离。
本质上，您假设每个对象都是 5 维中的一个点，并寻找最近的点（即：距离最短）。
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).