https://github.com/grindelfp/k-nearest-neighbors-exericise

An exercise on k-nearest neighbors algorithm.
https://github.com/grindelfp/k-nearest-neighbors-exericise

ipynb k-nearest-neighbors machine-learning python

Last synced: 7 days ago
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An exercise on k-nearest neighbors algorithm.

• Host: GitHub
• URL: https://github.com/grindelfp/k-nearest-neighbors-exericise
• Owner: GrindelfP
• License: mit
• Created: 2024-03-25T17:06:27.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-03-25T17:31:07.000Z (8 months ago)
• Last Synced: 2024-11-13T06:41:31.784Z (7 days ago)
• Topics: ipynb, k-nearest-neighbors, machine-learning, python
• Language: Jupyter Notebook
• Homepage:
• Size: 679 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.adoc
  • License: LICENSE

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README

        
= K-Nearest Neighbors excercise =

A small exercise on understanding of concept of K-Nearest Neighbors algorithm. The exercise follows this steps:

1. create 3 groups of 140 2-dimentional points on a 2-dimentional plane

2. experiment with cluster standart coefficients

3. develop a function implementing K-Nearest Neighbors algorithm

4. test the function on some additional points and show them on the plane

The task is done using Google Colab.