Implementation of K-Nearest Neighbours (KNN) from scratch
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Updated
Mar 21, 2021 - Python
Implementation of K-Nearest Neighbours (KNN) from scratch
The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems
recognize mouse-written numbers using KNN, Neural Network, and Convolutional Neural Network models
This repository contains the code for a K-Nearest Neighbors (KNN) model built to classify customer segments in Türkiye using the teleCust1000T dataset. The project includes data cleaning, visualization, feature scaling, model training, and evaluation with accuracy metrics.
You Say "HI" , this program classifiies it .....
From Scratch
A KNN algorithm based on the HVDM distance metric powered by decision trees using Weka libraries as a complement developed in Python.
This project creates an image of various points, with each pixel colored according to that pixel's distance to the nearest couple of points and their respective colors.
Konu: Kendi Belirlediğimiz bir problem için uzman sistem oluşturma
In this notebook we'll see how to use KNN to classify the IRIS Flowers.
Fast k-NN graph construction for slow metrics
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