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 ...

As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...

Abstract: In this paper we propose an optimized version of the PCA algorithm by using genetic algorithms and the KNN technique with applications in the classification of image classes. The algorithm ...

This cross-sectional study was conducted between June 2011 and January 2012. The participants were randomly selected using a simple random sampling technique. Seven commonly used machine learning ...

Abstract: ${K}$ -nearest neighbors (KNN) algorithms are widely used for indoor fingerprint positioning, but conventional KNN algorithms usually adopt received signal strength (RSS) similarity as a ...

Though we’re living through a time of extraordinary innovation in GPU-accelerated machine learning, the latest research papers frequently (and prominently) feature algorithms that are decades, in ...

knncolle is a header-only C++ library that collects a variety of different k-nearest neighbor algorithms under a consistent interface. The aim is to enable downstream libraries to easily switch ...