# 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:**

Age | Marks | |

Sameed | 10 | 90 |

Shah zeb | 6 | 95 |

**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;

Sameed | Shah zeb | |

Sameed | 0 | 6.40312 |

Shah zeb | 6.40312 | 0 |