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Euclidean distance in data mining

Last modified on December 9th, 2018 at 9:17 pm

What is the Euclidean distance?

Euclidean distance is a technique used to find the distance/dissimilarity among objects.

Example:

 AgeMarks
Sameed1090
Shah zeb695

Formulae:

Euclidean distance (sameed, sameed) = SQRT (   (X1 – X2)+ (Y1 -Y2)2   ) = 0

[quads id=2]

Euclidean distance (sameed, sameed) = SQRT ( (10 – 10)+ (90 -90)2) = 0

Here note that (90-95) = -5 and when we take sqaure of a negative number then it will be a positive number. For example, (-5)2 = 25

Euclidean distance (sameed, shah zeb) = SQRT ( (10 – 6)+ (90 -95)2) = 6.40312

Euclidean distance (shah zeb, sameed) = SQRT ( (10 – 6)+ (90 -95)2) = 6.40312

Euclidean distance (sameed, sameed) = SQRT ( (10 – 10)+ (90 -90)2) = 0

Euclidean Distance is given below;

 SameedShah zeb
Sameed06.40312
Shah zeb6.403120

 

Prof. Fazal Rehman Shamil
Researcher, Publisher of International Journal Of Software Technology & Science ISSN: 2616-5325
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