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
This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.
recognize mouse-written numbers using KNN, Neural Network, and Convolutional Neural Network models
This GitHub repository hosts the project report and analysis code on investigating lifestyle habits and medical conditions influencing diabetes prevalence. Utilizing data from the CDC's Behavioral Risk Factor Surveillance System survey, the project explores correlations and predictive models for diabetes risk.
This is a Python repository implementing a K-Nearest Neighbors (KNN) algorithm for predictive modeling using car data.
A simple python script that implements K Nearest Neighbors Algorithm. University Assignment
Konu: Kendi Belirlediğimiz bir problem için uzman sistem oluşturma
Samsun Innovation Campus 301 AI (HR Data Analysis ,Visualization and modelling)
From Scratch
A KNN algorithm based on the HVDM distance metric powered by decision trees using Weka libraries as a complement developed in Python.
A complete Guide to K-Nearest-Neighbors with Applications in Python
In this notebook we'll see how to use KNN to classify the IRIS Flowers.
Hello, in this code I designed the KNN algorithm myself and rewrote it from scratch. I wanted the source code to be available in case I need an improvement in the future. Thanks to this code, I am stepping into learning SOLID principles.
Performed Clustering Analysis using SAS v9.4 on Power Usage & Consumer Goods Data to draw insights about the dataset.
The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems
For this project, we'll be using a non-parametric classification method, k-nearest neighbors algorithm, to compress images.
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.
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.
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