NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

Abstract: Optimizing the K value in the K-Nearest Neighbor (KNN) algorithm is a critical step in enhancing model performance, particularly for tasks related to classification and prediction. The Elbow ...

Geeta Gandbhir’s film examines the killing of a Florida woman and “stand your ground” laws, but the issues it raises are bigger than those statutes. By Alissa Wilkinson When you purchase a ticket for ...

Contrastive image and text models face significant challenges in optimizing retrieval accuracy despite their crucial role in large-scale text-to-image and image-to-text retrieval systems. While these ...

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...

The k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big ...

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...

This repository contains a Python implementation of a K-Nearest Neighbors (KNN) classifier from scratch. It's applied to the "BankNote_Authentication" dataset, which consists of four features ...

Source codes and datasets used for the undergraduate capstone project entitled "Machine Learning Algorithms for the Detection of GPS Spoofing in Intelligent Transportation Systems" ...