The experts at irishracing.com have fired up their supercomputer to assess which horse has the best chance of winning the Gold Cup ...

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 the ...

Nearest neighbour classification techniques, particularly the k‐nearest neighbour (kNN) algorithm, have long been valued for their simplicity and effectiveness in pattern recognition and data ...

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) ...

Over the past few years, we observed a rethinking of classical artificial intelligence algorithms from a quantum computing perspective. This trend is driven by the peculiar properties of quantum ...

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

Abstract: An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k-nearest neighbor algorithm (kNN) which usually identifies ...