ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

ABSTRACT: The objective of this work is to determine the true owner of a land- public or private- in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...

A Pew Research Center survey suggests that they may like you more than you realize. By Arnesa A. Howell Whether you’re in a city, a suburb or a rural area, living among people you trust can mean the ...

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...

The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on diagnostic ...

This repository contains the implementation of a hardware-accelerated K-Nearest Neighbors (KNN) algorithm using Verilog on an FPGA. The project includes performance and timing analysis using Quartus, ...

Abstract: Data mining is the process of handling information from a database which is invisible directly. Data mining is predicted to become a highly revolutionary branch of science over the next ...