Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, coding process, and practical examples to help you understand how KNN works ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

Abstract: Privacy-preserving k-nearest neighbor (PPkNN) classification for multiple clouds enables categorizing queried data into a class in keeping with data privacy ...

The Kansas State Wildcats have themselves a potential gem with their latest signee. Three-star offensive lineman Will Kemna has signed his letter of intent and is with the Wildcats for the foreseeable ...

In order to study the relationship between surrounding rock mass properties and tunnel excavation parameters, the EPB machine operational data were collected from rings 823 to 873. The operational ...

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...

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, ...