Skip to content

A Python implementation of the K-Nearest Neighbors (KNN) algorithm for classification and regression tasks, including sample datasets and usage instructions

Notifications You must be signed in to change notification settings

PrachetasPathak/knn-implementation-python

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 

Repository files navigation

knn-implementation-python

A Python implementation of the K-Nearest Neighbors (KNN) algorithm for classification and regression tasks, including sample datasets and usage instructions Description This repository contains a Python implementation of the K-Nearest Neighbors (KNN) algorithm, a simple and effective machine learning method for classification and regression. The program includes customizable parameters and sample datasets for easy testing.

Features KNN Algorithm:

Supports classification and regression tasks. Allows tuning of parameters like the number of neighbors (k) and distance metrics. Dataset Support:

Includes options to use built-in datasets or load custom datasets. Provides functionality to split data into training and testing sets. Performance Metrics:

Outputs accuracy for classification tasks. Calculates mean squared error for regression tasks.

About

A Python implementation of the K-Nearest Neighbors (KNN) algorithm for classification and regression tasks, including sample datasets and usage instructions

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages