Abstract: K-Nearest Neighbors (KNN) is a basic model in a ML field used for classification or prediction analysis owing to its efficiency. The following paper will be a survey paper focused on ...

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 ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

Vicinity is a light-weight, low-dependency vector store. It provides a simple and intuitive interface for nearest neighbor search, with support for different backends and evaluation. There are many ...

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 ...

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 ...

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 ...

Each implementation is optimized for its respective computing paradigm while maintaining classification accuracy.