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 ...
Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, coding process, and practical examples to help you understand how KNN works ...
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 ...
1 Yibin University, School of Computer Science and Technology, Yibin, China 2 Southwest Petroleum University, School of Computer and Software, Chengdu, China Network security is the core guarantee for ...
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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) ...
Introduction: Atopic dermatitis (AD) is an allergic disease with extreme itching that bothers patients. However, diagnosing AD depends on clinicians’ subjective judgment, which may be missed or ...
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