Minkowski distance is a metric in a normed vector space. Minkowski distance is used for distance similarity of vector. Given two or more vectors, find distance similarity of these vectors.
Mainly, Minkowski distance is applied in machine learning to find out distance similarity.
Input : vector1 = 0 2 3 4 vector2 = 2, 4, 3, 7 p = 3 Output : distance1 = 3.5033 Input : vector1 = 1, 4, 7, 12, 23 vector2 = 2, 5, 6, 10, 20 p = 2 Output : distance2 = 4.0
Note : Here distance1 and distance2 are almost same so it will be in same near region.
- Python | Calculate distance and duration between two places using google distance matrix API
- Python | Calculate Distance between two places using Geopy
- Python | Distance-time GUI calculator using Tkinter
- Closest perfect square and its distance
- Rearrange a string so that all same characters become d distance away
- Minimum Distance Between Words of a String
- Find maximum distance between any city and station
- Find a rotation with maximum hamming distance
- Difference between Distance vector routing and Link State routing
- Lexicographically smallest string whose hamming distance from given string is exactly K
- Important differences between Python 2.x and Python 3.x with examples
- Reading Python File-Like Objects from C | Python
- Python | Merge Python key values to list
- Python | Sort Python Dictionaries by Key or Value
- Python | Set 4 (Dictionary, Keywords in Python)
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.