What is the Euclidean distance?

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

Example:

Formulae:

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

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

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

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

Euclidean Distance is given below;

Download Excel File Calculations

This file contains the Euclidean distance of the data after the min-max, decimal scaling, and Z-Score normalization.

Click Here to Download 

Euclidean distance after the min-max, decimal scaling, and Z-Score normalization

Let’s see the “Euclidean distance after the min-max, decimal scaling, and Z-Score normalization”.

Video Lecture

Next Similar Tutorials

1. Proximity Measure for Nominal Attributes – Click Here
2. Distance measure for asymmetric binary attributes – Click Here
3. Distance measure for symmetric binary variables – Click Here
4. Euclidean distance in data mining – Click Here Euclidean distance Excel file – Click Here
5. Jaccard coefficient similarity measure for asymmetric binary variables – Click Here